Interagency Ocean Observation Committee (IOOC)€¦ · Web view2012/10/31 · The Summit Report will finally be published (online) with the Community White Papers (CWP) as appendices.

To: IOOS CommunityFrom: IOOS Summit Co-chairs

Subject: Draft Summit Report Review

We are two weeks from the IOOS Summit in Herndon, VA. We look forward to your input!

An enormous amount of effort has been expended since May to prepare background documents for the IOOS Summit. Much has been learned and accomplished from the preparation of more than 100 Community White Papers, the five synthesis chapters, recommendations, the Summit program, and a Summit Declaration.

Let us describe the status of the primary documents coming out of the Summit.

The IOOS Summit Report is in draft form without an executive summary or introduction. What you find attached are the five synthesis chapters with a short “readers guide” (see next page).

The Summit Report will finally be published (online) with the Community White Papers (CWP) as appendices. The CWP are still under review and comments to the authors will likely be returned in November. The review is “friendly” in the sense that reviewers task is to provide helpful comments and suggestions to improve the papers. No CWP will be cut from the Report based on this review.

An Executive Summary of ~10 pages will be part of the final Report and also serve as a stand-alone high-level summary of IOOS in 2013. This will necessarily be constructed after the Summit based on the final Summit Report, recommendations, and Summit Declaration.

The Summit Declaration will be presented and distributed in draft form at the Summit and posted online. It is a two-page high-level statement from the Summit. The community will have the opportunity both at the Summit and virtually to suggest amendments to the Declaration.

Please provide any recommendations/actions that should come out of the summit, and the most important points for inclusion in the Executive Summary. If you have edits to the five synthesis chapters we encourage you to provide them online at the IOOC website http://www.iooc.us/summit/report.

DRAFT:IOOS® SummitReport

Version 2-2

31 October, 2012

http://www.iooc.us/summit/report

A Readers Guide to the DRAFT IOOS Summit Report

Between now and the end of 2012 we plan to finalize this report. In final form it will consist of an Executive Summary (not yet drafted), and Introduction (not yet drafted), synthesis chapters, and appendices including the final versions of the Community White Papers (CWP: now available in draft form at the IOOS Summit web site).

This initial draft version contains the synthesis chapters as they stand at the end of October 2012. We must all recognize the enormous amount of work has been done to distill material from the CWPs and writing teams. Those who read the document will also recognize that more work is necessary to improve, refine, and finalize the synthesis of IOOS that is presented and will be discussed at the Summit. The process began with constructing five chapters: Progress During the Past Decade; User Engagement and Requirements; Observing Systems Capabilities: Gap Assessment and Design; Integration Challenges and Opportunities; and a Vision for the Future.

In this draft we present first the vision for IOOS followed by the chapters on progress and user needs, the observing system, and finishing with integration. Since it is a large document and your time may be limited, you may wish to focus on only a few chapters (though we encourage full engagement!).

Reading the “Vision for the Future” is a priority for all Summit participants. A critical outcome of the Summit is development of a common vision for the coming decade of work. That’s why we put the vision first in this document.

If your interest is primarily as a user of IOOS, please help us hone the messages on user needs (chapter 3 of this document).

If your interest is primarily on an observing system component, please help us hone the messages on progress, status and plans for the observing system (chapter 4 of this document).

An overarching theme of the summit is integrating the global, national, and regional components of ocean observing into a more seamless IOOS. Please help us hone the messages on integration (chapter 5 of this document).

There will be Summit presentations, panels, and break-outs that roughly parallel the chapter structure. These preparations are meant to maximize your engagement and feedback at the Summit through your preparation with this draft document.

Happy Reading!

1 DRAFT IOOS Summit Report: October 31, 2012

EXECUTIVE SUMMARY

THIS WILL BE WRITTEN BASED ON

RESULTS OF THE SUMMIT


Table of Contents

Chapter One: A Vision for the Future...............................................................51. Vignettes....................................................................................................................................... 5

2. Drivers for a New Decade of Ocean Observing.................................................................6

People and Culture...........................................................................Error! Bookmark not defined.

Commerce and Economy................................................................Error! Bookmark not defined.

Technology and Communications................................................Error! Bookmark not defined.

Politics and Governance.................................................................Error! Bookmark not defined.

U.S. Public Policy Drivers.............................................................Error! Bookmark not defined.

3. The Challenge............................................................................................................................... 8

4. The Vision.................................................................................................................................... 10

5. Conclusions................................................................................................................................. 11

Chapter Two: Progress During the Past Decade...........................................121. History and Structure of U.S. IOOS...................................................................................... 12

Early History................................................................................................................................................... 12

The Airlie House Workshop..................................................................................................................... 13

Structure of U.S. IOOS.................................................................................................................................. 16

U.S. IOOS National Program Office; the Integrated Coastal Ocean Observing Act of 2009............................................................................................................................................................................... 17

2. Success Stories / Delivering the Benefits.........................................................................18

3. Assessments and Accomplishments..................................................................................22

4. Introspection............................................................................................................................. 33

Chapter Three: User Engagement and Requirements............................341. Introduction............................................................................................................................... 34

2. User Engagement and Requirements................................................................................36

Hallmarks of Successful User Engagement...........................................................................................36

User Engagement............................................................................................................................................ 38

User Requirements......................................................................................................................................... 39

3. Current Challenges.................................................................................................................. 40

4. DRAFT Recommendations................................................................................................... 45


Chapter Four: Observing System Capabilities -- Gap Assessment and Design.......................................................................................................................... 47

I. Introduction................................................................................................................................ 47

2. Overarching Issues................................................................................................................... 48

3. The U.S. IOOS Functional Subsystems................................................................................53

DMAC Structure..............................................................................................................................................59

4. Summary..................................................................................................................................... 63

5. DRAFT Recommendations.................................................................................................... 64

Chapter Five: Integration Challenges and Opportunities......................661. Introduction............................................................................................................................... 66

2. The “I” in IOOS............................................................................................................................ 66

3. Challenges to, and Opportunities for, Improved Integration....................................68

Overall Integration.........................................................................................................................................68

Observations Subsystem............................................................................................................................... 68

Data Management & Communications Subsystem.............................................................................70

Modeling & Analysis Subsystem................................................................................................................73

4. DRAFT Recommendations.................................................................................................... 74

Chapter Six: The Way Forward/Recommendations...............................76

Appendix A: Acronyms...............................................................................................................77

Appendix B: DRAFT Glossary of Terms..............................................................................81

Appendix C: Authorship Table...............................................................................................85

Appendix D: DRAFT References and Reading List........................................................86

Appendix E: Synopsis Table for Chapter One..................................................................95

Appendix F: Draft Chapter Three Summary Table.....................................................104


Chapter One: A Vision for the Future

1. Vignettes.

The year is 2022 ...

The owner of a fleet of charter fishing boats in Oregon contacts his customers to tell them that the departure time for their albacore trip next week will be an hour earlier to ensure they get to the best fishing grounds. That call is based on the predictions that he gets as part of his subscription to an ocean information service.

The Chief Operating Officer of a global shipping line reviews quarterly revenue projections based on a change in optimal track ship routing for the fleet. A reliable tailored projection of when passage will be possible for six weeks through the Northern Sea Route of the Arctic Ocean, has been made available to him in March of that year.

A public health warning has been issued to hotels, chambers of commerce, hospitals and clinics, in three coastal counties of Florida. They are informed of a harmful algal bloom, with potential health impacts, which will occur next week. Emergency medical supplies are shipped to the area, and alternative vacation options are sent to prospective travelers.

Immediately upon the grounding of a New Panamax class container ship in an Asian port, a fleet of unmanned surface vehicles, gliders and autonomous underwater vehicles is deployed to monitor the release and dispersion of fuel oil. The vehicles are operated by, and their data collected by a commercial marine response service.

A major canoe and kayak tournament is scheduled to take place from Maine to Rhode Island during the last summer months: this is a major outdoor recreation and tourism event drawing 30,000 visitors from around the continent. Weather and sea state forecasts are enable critical to the successful planning of the event as well as the multiple scheduled guide-led tours. Smart phone apps provide tournament participants hourly updates on sea conditions.

Water reservoir managers as well as emergency managers use the community of observing systems in concert with the National Weather Service to apply a doubled winter snowmelt forecast for the upper Mississippi River Basin. That outlook product also supports improved barge scheduling down the River system, in fact doubling the movement of breakbulk goods from the Great Lakes through New Orleans and through the Panama Canal. An additional derivative of that product itself serves as an outlook for northern Gulf of Mexico hypoxia. The six month lead time allows Soil and Water Conservation Districts in concert with water reservoir managers to not only anticipate flood but to manage the timing and rate of releases in a way that leads to the first ever improvement in the frequency, extent and duration of the hypoxic events.


Parallel ongoing revolutions in communications, knowledge processing and transportation are realigning the standing of countries all over the world, including the relative position of the United States among the leading societies and economies of the 21st century. Indeed, some have characterized the challenge of the future in terms of defining the role of a “Blue Economy” in addressing the key applications of water, food, coastal real estate, and energy (Michael B. Jones, “Promoting the Blue Economy: The Role of Maritime Technology Clusters”, Mains’l Haul, V. 38: 138-147, 2012). The dramatic rate and scale of this change that formerly played out over multiple decades can now be seen within a few years.

2. Drivers for a New Decade of Ocean ObservingDuring just the initial decade of design and implementation of IOOS®, the world has been

shaken with change affecting economies, security and environment. Data processing

measurement has moved from kilobytes to yottaflops. Pocket-sized smartphones are

ubiquitous, and social networks connect people around the globe instantaneously. The

awesome power of nature, as seen from ocean-based earthquakes and associated tsunamis,

along with notable environmental disasters such as large oil spills, have affected trillions of

dollars of wealth and commerce. Ever larger merchant ships deliver greater cargoes to

more destinations, and the capacity of the Panama Canal is about to double. The relatively

open access of ports and the low cost of maritime commerce leave large gaps in security

protocols for most of the world’s most intensely populated and commerce-filled areas.

In short, the drivers that inspired the development of IOOS ten years ago have largely acted

as anticipated, except that change has been greater and faster than projected. With the

world working to come out of a global recession, there is no reason to doubt the pace and

rate of this change to continue to increase. The drivers listed below will continue to

influence the speed and direction of development. Moreover, each of these sets of drivers

is intertwined with the others.

People and Culture

The world population today is 7 billion people – up a billion over the last ten years, and

projected to increase by another billion in the next ten. As anticipated, people have

increased their movements towards coastal areas all over the globe. In addition, the rate of

increase in household wealth around the globe is much greater than the rate of increase in

population. However, the United States is seeing only low-to-medium growth. Emerging

large economies such as China, India, Brazil and Indonesia are leading the way; and many

smaller economies are experiencing strong growth. As a result of instantaneous


communications, people around the world are more aware of other societies and cultures,

contrasting value paradigms, and inequality of prosperity.

In this world of change, information will become an increasingly valuable commodity. And

because of the role of maritime commerce, vulnerability to ocean-related natural disasters

and the need to provide security for coastal populations, and food and water for a larger

population, information about the oceans becomes just as critical as other data.

Commerce and Economy

The role that maritime commerce plays in our national economy is often underappreciated.

The role that it plays in coastal economies is essential to the vitality of our largest

communities. 99% of the volume of U.S. foreign trade, and 62% by value, enters or leaves

on a ship. Movement of goods through ports is inextricably linked to national supply

chains for virtually every type of goods and merchandise.

One of the hallmarks of the new economy is the fluid, rapid and enormous flow of capital

around the globe. Information primes the pumps of capital flow. Investments in ocean-

related services depend on reliable data and information, and private capital will thus

require ocean and coastal observation products. In this kind of world, data becomes a

commodity with economic value to investors; and ocean observing data are no different.

The focus of investment in oceans and coastal resources is broadening beyond petroleum

exploitation, fisheries, recreation and tourism. While these sectors continue to be

important, new technology and increased demand are fueling the growth of the ocean

energy sector, including wind, wave and tidal power – all requiring reliable and sustained

ocean data. And the growth in all of these sectors places greater emphasis on insurance

products that can only be priced properly when sufficient ocean information is readily

available.

Technology and Communications

The ability to take advantage of the knowledge, intellect and experiences of billions of

people is a key driver, made possible by improvements in technology and communications.

Information visualization and real-time access to an explosively increasing set of products

and services (think of Yelp, GoTo Meeting, and Groupon on steroids!) means IOOS data will

be accessible and interpretable by a vastly diversified user base. Community open source


platforms and crowd sourcing will take cloud computing capabilities to a “new normal” of

data analysis, adaptive sampling and product development

Politics and Governance

It is widely acknowledged that our national governance system is having significant

difficulty determining the direction that policy should take relative to economic

intervention, regulation, and the role of government in public and private life. The

economic downturn/Great Recession during the past 5-10 years has raised the priority for

job creation. For more than a decade, national policy has also focused on security. Jobs,

economic policy and security have been the drivers for high priority initiatives.

The late Admiral James D. Watkins, Chairman, U.S. Commission on Ocean Policy and Co-Chair, Joint Ocean Commission Initiative, stated in 2007 “It is now obvious that enhanced and integrated observing systems are a key element underlying a robust ocean and climate science strategy…A sustained, national Integrated Ocean Observing System (IOOS), backed by a comprehensive research and development program, will provide invaluable economic, societal, and environmental benefits, including improved warnings of coastal and health hazards, more efficient use of living and nonliving resources, safer marine operations, and a better understanding of climate change. However, the value of this system will be fully realized only if an adequate financial commitment is also provided to support integrated, multidisciplinary scientific analysis and modeling using the data collected, including socioeconomic impacts. Unfortunately, support for the lab and land-based analysis of the data derived from these systems is often inadequate, diminishing the value of these programs, while support for socioeconomic analysis is virtually nonexistent.” Admiral Watkins also pointed out: “While there is a continuing effort to integrate programs and activities, it is the exception not the rule. In addition, the budget process often discourages interagency cooperation as funding for multi-agency programs is subject to cuts or reductions during internal agencies budget negotiations, compromising the integrity of the broader strategy and promoting further competition among federal and nongovernmental players.” (Testimony before the Committee on Commerce, Science, and Transportation, Subcommittee on Ocean, Atmosphere, Fisheries, and Coast Guard, U.S. Senate, Washington, D.C May 10, 2007).

As government budgets face increasing downward pressures, and innovation allows for lower cost ocean observing technologies, likelihood of expanded private sector capacity is increased. There are a range of opportunities and challenges IOOS faces in balancing the policy of open access to data, generating the most economic activity and ability for these companies to be part of IOOS and still maintain profitability.

The private sector will play an increasing role in ocean observing. As the various economic, technical and political drivers become more influential, the importance of ocean and coastal data and information will be driven by demand from the private sector, and the


relative burden for funding will shift accordingly. But private sector investments will require a greater ownership of the ocean, coastal and Great Lakes observing enterprise, in the sense of being able to influence the structural and policy decisions that govern the system, while ensuring that the public good is held paramount.

U.S. Public Policy DriversOver the last ten years, the national government in the United States has recognized the importance of ocean and coastal observing, and codified its commitment to a sustained and integrated system. Over the next ten years, public policy will extend this attention to a demand for accountability. Congress and local jurisdictions will ask for measures of effectiveness in safety, security, economic development and general public welfare. Advances in scientific understanding will increasingly be subject to political manipulation. Just as the seemingly esoteric analyses of carbon cycling of years past have become fodder for partisan policy dialogue, the observations of coastal and oceanic phenomena may also fall subject to exaggerated and inaccurate misinterpretations. As a community we should proactively preempt such developments.

3. The Challenge For years information service providers have acknowledged that 'content is King'. If a service provider has the technology and the employee base to deliver services but has no content, that service provider will soon be out of business. The boom in content providers has shown that people are consumers of all types of information and this data explosion is continuing. Social media has become a leading source of information for people to make decisions quicker than they have ever done so before. At issue, however, is the accuracy and reliability of the information that travels so quickly. Consequently, many decisions are made in error because of inaccurate information. So while 'content is king' reigns true to many information services providers, further clarification is needed to describe the content as 'accurate'. Without accurate information being provided to drive decision making, confidence in information service providers would plummet and drive them out of business.

Like any successful business the supply chain must be managed well in order to keep commerce flowing. This supply chain also applies to information relating to the ocean, its state and forecasts of its condition. The accuracy of this information is critical to enable international trade, transportation and protection of our coastlines. Since ocean-related and near-ocean commerce accounts for so much of our nation's Gross Domestic Product (GDP), the more we know about the ocean the more our nation can maximize its potential and grow our economy.

People need technology and access to the right information so they can make the best decisions possible, wherever they are and whenever they need it. Most people do not know when they will need critical information or what kind of information they will need until they get into a situation where decisions (perhaps life-saving) need to be made. Many times whatever situation develops or hazard presents itself a complete decision tree has not been thought through in advance.


Today’s complex environment is being monitored by satellites, sensors on the ground, and in the ocean by drifting, moored, and autonomous vehicles. Atmospheric profile measurements are collected by planes, balloons and unmanned aerial vehicles being launched and radars catching just about every storm that develops. The amount of observations that are collected on the state of the ocean and atmosphere is impressive. Yet as storms develop and intensify, they sometimes unleash unexpected power that affects millions of people in a short period of time. The public may even express themselves as frustrated that they never received any warning that this storm was headed their way…even if the information was out there…it just didn’t reach them in time or at all. The information delivery pathway to serve citizens is incomplete.

Weather forecasters still have a difficult time determining precisely when a tropical system, spinning up in the tropical ocean, evolves into a tropical storm or transitions from a tropical storm into a hurricane – we have yet to understand fundamental questions about such intensifications. It takes observations from both satellite and airplanes flying into the storm to accurately determine its strength and a future IOOS® should offer proactive alerts and messages when certain criteria are met to satisfy the needs of a broad base of users. This is a system that evolves with technology and is responsive to the needs of the people.The need for real-time, actionable information is critical during day-to-day and emergency response operations where multiple jurisdictions and disciplines interact. Plenty of homeland security-related information exists at the local, tribal, state, and Federal levels, but since equipment investment decisions have been made based on the specific operational needs of individual agencies without benefit of a national strategy or standards, this information is often trapped in silos. As a result, potentially critical information often does not make it into the hands of the people who need it the most.In short, our challenge is to build a system that is:

Operationally reliable Economically sustainable Politically defensible Technologically evolvable

4. The VisionThe world defined by the examples at the start of this chapter will be enabled by the drivers thatwe've defined, and guided by the policies that pertain to environmental data and information. However, the realization of this vision can take many shapes. Just as over a hundred differentcountries deploy different forms of national weather services, we expect that many different paradigms can emerge successfully. We know, however, that certain 'boundary conditions' must exist to define a successful enterprise of ocean observing. We believe that vision will be definedby the following characteristics:


The ocean observation services that are provided will be "full spectrum". There's a quip that it’s easy to establish a weather service since you only need to monitor three kinds of data: pressure, temperature and moisture! Valid or not, this perspective calls to the fore the need to attend to scores of variables in a robust ocean observing system. While the value of real-time observations of ocean surface pH might be less relevant to commercial shippers, those same data will be of paramount importance to coastal shellfish hatcheries. The enterprise of services dependent on ocean information will demand that the full array of relevant observations be operationalized. The priorities for tailored observations will be driven by market demands, but all observation types will have the potential for full transition to market.

The ocean observing system will be a public-private enterprise. Public sector support will be insufficient to support all applications, and private investment will not tolerate footing the bill for what is arguably largely a public good. In this context, substantial national public investment will remain needed to ensure a core set of measurements of baseline variables remains intact. In addition to this continued federal investment, partnerships of new sorts will emerge, allowing a legal co-mingling of resources (with, of course, concomitant authorizations through revised economic policies and regulations). A risk-tolerant foundation of individual ('angel') and collective (venture capital, or crowd funding) investors will recognize a meaningful return on investment for the added value contribution to a publicly funded foundation of observations and services. Forms of industry cooperatives (as exist in many natural resource industries such as forestry) will form to support those sector-specific capabilities needed to enhance their bottom line. These private investment-backed activities will initially establish a broad array of creative business plans, a handful of which will become standard models for the industry (not unlike the evolution seen in information services over the last two decades). Ultimately a commercial enterprise of equity valuation in excess of $10B will emerge, with a workforce exceeding 10,000 in the United States alone (this is compared to data regarding the cost and value of the weather enterprise, as shown for example at www.sip.ucar.edu). This will, by necessity, be a global commercial enterprise of data acquisition, assimilation and application, information dissemination, and ocean product derivation, with full international interoperability for those who succeed - think of the telecommunications example as an analog, in which independent solutions ultimately had to become integrated to satisfy the needs of the market.

The ocean observing enterprise will be expressed through a new system of governance. A wholly different concept will have to emerge, that engenders sustained operations and investment value. Several concepts will need to be invoked to ensure operational configuration control,


requirements validation and management, research oversight, infrastructure recapitalization priorities and system refresh, as well as basic operations and maintenance. Several governance concepts will be adopted such as the use of Indefinite Delivery/Indefinite Quality (IDIQ) acquisition tools, establishment of public corporations’, deployment of Government Owned Contractor Operated (GOCO) principles, not to mention traditional corporate oversight. The governance system will provide accountability to the taxpayers and the stockholders.

The ocean observing system will promote the establishment of new models for workforce development. The breadth of skill sets, combined with the logistical challenges of operating to full ocean depth, at all times, throughout the globe will demand some special approaches to education, as well as access to knowledge. The community can tap into decades of experience in training weather forecasters and sensor engineers, while the capabilities for knowledge transfer enabled by broad band communications will open up opportunities for on-site educational opportunities (envision a systems engineer at an ocean observations site on the Pacific coast getting trained on buoy operations through a teleconnection to an oceanographic institution in Florida)

5. ConclusionsOur society is at a seminal point in the development of a class of products and services based onocean observations. We envision an enterprise of ocean observations that builds on xtraordinary successes to date, and merges with expected developments. Ultimately, we foresee a capabilityutilizing and delivering products from ocean observations that are fully integrated into theculture of our society, and is considered a non-negotiable component of our ability to enhance the lives, livelihoods and quality of life of future generations.

Chapter Two: Progress During the Past Decade1. History and Structure of U.S. IOOS

Early HistoryThe oceans are of fundamental importance to the health, national security and economy of the United States. Decades of focused investments in ocean observing and predicting have produced numerous examples of substantive societal and economic benefit resulting from improved


knowledge of ocean parameters and behavior. However, more complex and difficult questions about the ocean, particularly in the coastal regions, remain to be answered. Addressing these more complex issues requires innovative approaches to stimulate collaborative ventures between academia, industry, and Tribal, local, state and federal government entities. Recognizing this, beginning some two decades ago, the United States embarked on a series of efforts to define a path towards developing an optimal ocean observing, prediction, and product development/delivery system capable of addressing societal needs.

Time Line

1997: NOPP established, called for US IOOS1998: US GOOS steering team formed2000: Ocean.US established2002: Airlie House WorkshopSept 2004: US Ocean Commission- recommended US IOOSDec 2004: US Ocean Action Plan – committed to US IOOSDec 2006: NOAA Established an IOOS Program Office2008: National Federation of Regional Associations (NFRA) formally established2008:Ocean.US disestablished2009: ICOOS Act was passed2011: NOAA IOOS Program Office was recognized as US IOOS Program Office

For millennia, the oceans have stimulated commerce, industry and culture. Beginning in the middle part of the last century, as war and technology made global science more imperative, systematic study of the oceans and their processes began to be addressed broadly within the international scientific community. What these studies lacked was a comprehensive way to collect, manage and distribute observations to support the growing demand for ocean research.

During the latter part of the 1990’s, the Intergovernmental Oceanographic Commission (IOC), the United Nations Environmental Program, the World Meteorological Organization and the International Council for Science took the lead at the global level in planning for a coordinated effort to increase our understanding of the oceans through an improved system of observations, data management and communications, and modeling and analysis.1 From these efforts, the Global Ocean Observing System (GOOS) was born.

The ocean science community in the United States effectively led the multi-national processes to develop GOOS. As this effort was underway at the global level, two points were clearly recognized in the U.S. First, implementation of the coastal module for U.S. ocean observing, while paralleling the global efforts and providing data to them, would need to be done domestically. Second, the national interests of this country – security, economic, and

1 The IOC took the lead in hosting these efforts with its partner agencies within and outside of the U.N. system. Most of the seminal documents are contained in its electronic archives. See, e.g., <http://www.iocunesco.org/index.php?option=com_wrapper&view=wrapper&Itemid=100003>.


environmental – were sufficiently strong drivers for the U.S. to move forward to address its own particular concerns, regardless what was happening in the international community. Table1. The seven areas of societal benefit agreed upon as the drivers for IOOS.

Detecting and forecasting oceanic components of climate variability Facilitating safe and efficient marine operations Ensuring national security Managing resources for sustainable use Preserving and restoring healthy marine ecosystems Mitigating natural hazards Ensuring public health

The Airlie House Workshop

The initial focus of Ocean.US was on developing an initial plan to achieve the vision of a national IOOS which led to a major Workshop at Airlie House in Warrenton, Virginia from March 10-15, 2002 to develop a strategic design plan for a U.S. Integrated Ocean Observing System.

At this workshop, broad consensus was achieved regarding the vision and direction for U.S. IOOS. Consistent with the GOOS program, U.S. IOOS would contain both a global, open-ocean component, as well as a coastal component focused on this country’s Exclusive Economic Zone. Contributions to GOOS would principally be a responsibility of federal agencies, working as necessary with academic institutions, the states and the private sector. The coastal component would be addressed by a suite of core observations supported by federal agencies considered to be the “backbone” of the coastal system. Other entities, such as Tribal, state, regional and local governments, the private sector, academia and non-governmental organizations, would contribute observations to the coastal component; and with additional resources, would provide additional ocean observations to address particular regional needs. Regional institutions would have to be developed to provide coordination in their areas.

Thus, U.S. IOOS would be an end-to-end, heterogeneous, distributed system of linked elements, with organizational structures and interfaces developed where common good is identified. The concept of the end-to-end nature of the IOOS consists of the following, interrelated components connected by a two-way flow of information and data:

• The Observing Subsystem consisting of the platforms, sensors, instrumentation and techniques necessary to measure required parameters at the temporal and spatial scales relevant to the detection and prediction of particular user requirements, including to detect and predict changes in coastal indicators;

• The Data Management and Communications Subsystem which consists of the hardware and software to provide physical telemetry, exchange protocols and standards for quality assurance and control, data dissemination and exchange, archival, and user access; and


• The Analysis, Modeling and Applications Subsystem consisting of data assimilation and blending techniques, data and knowledge synthesis and analysis; and the procedures for translating data and knowledge into user-specified products.

A broad consensus was achieved at the Airlie House Workshop regarding the vision and direction for U.S. IOOS including identifying twenty high priority core variables necessary to meet the seven societal goals. This list of variables was codified in the US IOOS development plan, the IGOOS Coastal Theme Report and the GOOS – Coastal Module Implementation. An additional six variables have been added in the US IOOS Blueprint.


Table 2. The twenty-six high-priority core variables needed to meet the seven societal goals. Variables are shown in alphabetical, not priority order, and require further refinement by the community . (Blueprint, 2010)


Structure of U.S. IOOSAs we examine how best to sustain the integrated ocean observing effort, it is important to review the progress of the past decade toward the vision, goals and requirements of U.S. IOOS®.

Following the Airlie House Workshop, Ocean.US continued to engage federal agencies and the ocean observing community at large concerning development of U.S. IOOS at the national scale. Products were regularly developed focusing on system development planning, economic benefits, data management and communications, regional organizations, modeling and analysis, and other technical and organizational details.

Along with the activity specific to U.S. IOOS and Ocean.US, broader issues of ocean policy were playing out in the executive and legislative branches of the United States (US) government. The U.S. Commission on Ocean Policy released a report2 in September, 2004, and among many other recommendations highlighted and supported the development and implementation of improved ocean and coastal observing systems. In response to the Commission report, the President issued the U.S. Ocean Action plan that renewed the federal government’s commitment to ocean observing, and revised the governance structure for U.S. IOOS.

Funding the Regional Coastal Ocean Observing SystemsCoincident with the efforts of Ocean.US to provide national leadership in laying out a structure and direction to U.S. IOOS, efforts were under way to develop and support efforts in various regions of the U.S. to address specific requirements for coastal ocean observing. To initiate particular efforts, Congress provided funding to develop limited Regional observing system components; however these funds were used for specific projects at individual and groups of academic institutions. This resulted in a number of successes (e.g., the Gulf of Maine buoy network, a South East Costal Ocean Observing System providing buoys in North Carolina, South Carolina and Florida) that served to illustrate the basic soundness of the Regional approach. As well, under NOAA’s Coastal Services Center, competitive grants were awarded to 11 entities to establish initial Regional Associations (RA) to manage regional observing efforts. As the program matured, it was realized that for U.S. IOOS to survive, there needed to be formal funding within the Administration’s budget and that the Regional Associations needed to become a coherent network of Regional Coastal Ocean Observing Systems (RCCOOS). In October 2005, leading oceanographic research institutions and Center for Ocean Research and Education (CORE) signed a letter to agree to move away from earmarks and move towards an open, competitive approach to obtain funding that a formal budget line and national RCOOS consistency would require. In FY2008, funding for US IOOS was committed as part of the Administration’s budget. The funding of Regions transitioned from a series of Congressionally-directed awards to a competitive, peer-reviewed funding process to maximize taxpayer return on investment and transition from a variety of distinct, sub-regional observing elements to eleven, more cohesive regional systems directed toward common goals. NOAA administered the selection and funding process and provides the leadership, management, and oversight needed to ensure IOOS Regional activities develop in a manner consistent and compatible with national

2 “An Ocean Blueprint for the 21st Century.” The Commission was chaired by the late Admiral James Watkins. A parallel, privately-funded and –organized effort, the Pew Oceans Commission, came to many of the same recommendations at about the same time.


IOOS data management standards and infrastructure. This regional participation helps lay the groundwork for rapid expansion of data interoperability to provide, for the first time, widespread interoperable ocean data.

Ocean.US also recognized the need for regional collaboration and leadership to sustain coastal ocean observations. In 2003 it sponsored a summit to address requirements for the structure and functions of regional coordination. As a result of this summit, the Regional Associations (RA) were recognized as a part of the overall U.S. IOOS governance paradigm. In addition, the summit acknowledged the need for a National Federation of Regional Associations (NFRA) to help coordinate activities among the RAs and to facilitate collaboration with the federal agencies. Thus NFRA was formed and continues to play a strong role in supporting the diverse collaborations that are the fabric of U.S. IOOS.

Table 3. There are currently11Regional Associations within the U.S. IOOS Program.

Alaska (AOOS) Caribbean (CaRA) Central and Northern California (CeNCOOS) Gulf of Mexico (GCOOS) Great Lakes (GLOS) Mid-Atlantic (MARACOOS) Pacific Northwest (NANOOS) Northeast Atlantic (NERACOOS) Pacific Islands (PacIOOS) Southern California (SCCOOS) Southeast Atlantic (SECOORA)

U.S. IOOS National Program Office; the Integrated Coastal Ocean Observing Act of 2009Funding for IOOS was included in the Administration’s budget for the first time in FY2008. To provide a more focused leadership for federal agency partners, and to better align different sources of funding into a coordinated system directed at U.S. IOOS goals, NOAA established an IOOS Program Office within the National Ocean Service in late 2006.3 Recognizing the steps being taken by NOAA, the governing body recommended disestablishment of Ocean.US, placing greater emphasis on the need for Federal agency oversight of the program. This recommendation was accepted by its senior bodies in the federal ocean sciences governance structure; and on September 2008 Ocean.US was closed.

The next era of US IOOS began when the President signed the Integrated Coastal and Ocean Observation System Act of 2009 (ICOOSA). ICOOSA mandates the establishment of a National Integrated Coastal and Ocean Observation System, and provides for the federal government support to sustain it, designated NOAA as the lead federal agency. Structurally, the ICOOSA established the following:

3 NOAA is still the only agency to have taken the step of establishing a specific, internal organizational entity specifically to address U.S. IOOS. Given its mission to address questions of ocean science, this is perhaps to be expected.


http://www.ioos.gov/regions/secoora.html

http://www.ioos.gov/regions/sccoos.html

http://www.ioos.gov/regions/pacioos.html

http://www.ioos.gov/regions/neracoos.html

http://www.ioos.gov/regions/nanoos.html

http://www.ioos.gov/regions/maracoos.html

http://www.ioos.gov/regions/glos.html

http://www.ioos.gov/regions/gcoos.html

http://www.ioos.gov/regions/cencoos.html

http://www.ioos.gov/regions/cara.html

http://www.ioos.gov/regions/aoos.html

Council: Defined as the NORLC, functionally the National Ocean Council Deputy Level, for policy and coordination oversight

Committee: Establishes an Interagency Ocean Observation Committee (IOOC) to manage tasks such as budgeting, standards, protocols, and coordination

Integrated Ocean Observing System Program Office: Implementation and Administration of the system. Established within NOAA, with personnel from IOOC member agencies.

System Advisory Committee: Advises the NOAA Administrator and the Interagency Ocean Observing Committee.

ICOOSA recognizes the national and regional components of the system, with regional information coordination entities (essentially, RAs once certified) to take leadership in their areas. In 2011 the NOAA IOOS Program office was recognized by the IOOC and NFRA as the US IOOS Program Office. The US Army Corps of Engineers (USACE) established a liaison billet to this office. United States Geological Survey (USGS) provided a detailee for 1 year, who still today maintains a close working relationship with the IOOS Program Office.

Since 2009, the IOOC, the U.S. IOOS Program Office, the RAs, and National Federation of Regional Associations (NFRA), along with other partners and collaborators, have also achieved other significant objectives in developing the system. To note just a few highlights, there is now a formal policy on the public/private use of data; A Blueprint for Full Capability (Blueprint); RAs have developed coordinated build-out scenarios to meet the requirements of the coming decade, and the independent cost estimate is nearing completion.

2. Success Stories / Delivering the Benefits

The IOOS has proved to be a vital set of tools for tracking, predicting, managing, and adapting to changes in our coastal and ocean environment. IOOS has addressed safety, economic, and environmental issues of the United States, and there are many success stories over the past decade in all of these areas.

Increased observations to National Weather Service. Observations from NOAA and IOOS partners that supports global atmospheric modeling have been increased by 1000%. Much of these data come from unique Regional Association (RA) sources.

Supporting Oil Spill Response. The U.S. IOOS response to the April 2010 Deepwater Horizon oil spill in the Gulf of Mexico was threefold: observing technologies used in new ways to aid response; immediate access to non-federal data in the region impacted by the spill, and a project that tracked surface and subsurface oil. Satellite data and gliders provided new technologies to support oil spill response. It is a testament to the IOOS partnership that assets were brought from across the United States and that the data and models were immediately usable in the Federal emergency response, but this coordinated data management effort also revealed that sufficient baseline information was not available.

Japanese Tsunami. IOOS played a part in the warning and information flow of the March 2011tsunami wave’s reach to the United States. Nationally the Deep-ocean Assessment and Reporting of Tsunamis (DART) buoys and tide gauges provided vital information for adequate warning along U.S. coastlines. Regional Associations provided unique and critical observations, and saw five to ten-fold increases in


web-traffic demonstrating increased local public trust in the RA information. Coastal Ocean Dynamics Applications Radar (CODAR) SeaSonde radars located in Japan and California detected and measured tsunami current flows 10 to 45 minutes prior to the waves arrival at neighboring tide gauges,4 representing the first such tsunami observations made with radar technology.

Hurricane Monitoring and Forecasting. As Hurricane Irene moved through the Caribbean and along the East Coast of the United States in August 2011, non-Federal partners of US IOOS significantly augmented NOAA’s observing and forecasting capabilities. NOAA used the buoys from the Caribbean), Southeast, and Northeastern Regional Associations to track the Hurricane, initialize and verify forecasts. The United States Coast Guard, NOAA’s National Hurricane Center, and NOAA’s Weather Forecast offices in New England all used RA models to support local forecasts. As Irene progressed up the East Coast the Mid-Atlantic Regional Association collected and distributed high frequency radar data, glider routes and phytoplankton bloom monitoring, and delivered new forecasts to the New Jersey Board of Public Utilities. Underwater glider RU-16, deployed by the Environmental Protection Agency, N.J Department of Environmental Protection and Rutgers University, rode out the storm in deeper waters offshore and collected an unprecedented dataset from Irene that will inform forecast model development well into the future.

Storm Surge Display Program. The National Hurricane Center (NHC) runs a computerized model, called the Sea, Lake, and Overland Surges from Hurricanes (SLOSH), to predict storm surge. Through a U.S. IOOS customer project within NOAA, real-time water level and wind data were incorporated into the SLOSH Display. Since 2010, forecasters have access to time series graphs of water level observations, predictions, and winds, as well as Geographic Information System capabilities for displaying roads, populated areas and city boundaries, to display with surge information from the SLOSH model.

Search and Rescue. The USCG has added U.S. IOOS surface current monitoring data and forecasting to their Search and Rescue Optimal Planning System (SAROPS) and estimates that search areas can be reduced by as much as two-thirds over a 96 hour period with this data, leading to more lives saved and significantly lower search costs. A “Bar Forecast” that relies on U.S. IOOS wave data has reduced the number of USCG rescue incidents in the San Francisco area by 50%.

Supporting Emergency Responders. When USAIR 1549 landed in New York Harbor in January 2009, water temperature was a deadly 32ºF, river currents were swift, and rescue support data were critical. Within 30 minutes of the crash, MARACOOS partners’ were providing real-time oceanographic information to New York’s Office of Emergency Management (OEM). Following the crash, MARACOOS provided around the clock on-call assistance to various emergency agencies, including National Transportation Safety Board (NTSB), to support aircraft salvage operations.

Harmful Algal Blooms. There is now an operational Harmful Algal Bloom (HAB) bulletin for the Gulf of Mexico and pre-operational bulletins in the Northeast, Great Lakes and Northwest regions. The California Harmful Algal Bloom Monitoring and Alert Program, CeNCOOS and SCCOOS, jointly developed pier-based monitoring networks to enhance HAB data. Similar observations exist for Oregon and Washington but are not yet linked to HABMAP. In 2005, Woods Hole Oceanographic Institution (WHOI), working through NOAA’s Gulf of Maine HAB program, developed a coupled biological/physical ocean model to predict whether a HAB will occur and where it will move. This model and observations from NERACOOS predicted a bad HAB season in 2007, which triggered additional sampling and better tracking, allowing decreases in beach and fishing closures and saved

4 Lipa, Belina, et all; Japan Tsunami Current Flows Observed by HF Radars on Two Continents, Remote Sens. 2011, 3, 1663-1679; doi:10.3390/rs3081663, 3 August 2011


revenues. New technologies (Optical sensor on AUVs, the Environmental Sample Processor) are approaching transition to IOOS operations.

Safe Drinking Water. The Great Lakes provide drinking water to 22 million people, but face conflicting uses such as waste disposal, shoreline development, shipping, recreation and fishing. The Great Lakes Observing System (GLOS), with researchers at NOAA and Cooperative Institute for Limnology and Ecosystem Research (CILER), worked with local township and county officials to implement the Huron to Erie Connecting Waterways Forecasting System and developed a tool for managers to use when planning for spill events.

Storm Water Plume Tracking. SCCOOS provides local views of near real-time surface currents, modeled surf zone waves and currents, and meteorological observations to simulate Tijuana River plume tracking that support San Diego city managers’ decisions on where to conduct intense sampling for contamination, beach closures, and presenting information to the public.

Shellfish Industry Savings. Real-time data from offshore U.S. IOOS buoys provide early warning one or two days before cold, acidified seawater arrives in sensitive coastal waters where shellfish larvae are cultivated, allowing hatchery managers to schedule production to avoid these conditions. Based on improvements at several oyster hatcheries, the IOOS support is expected to contribute significantly to an estimated $45 million annually for coastal communities in Oregon and Washington.

Barge Operation Savings. Data from a PacIOOS buoy has saved fuel barge companies in Hawaii approximately $66,000 per year since 1977 in aborted trips by indicating ahead of time when ocean conditions are too rough to safely make oil deliveries. In addition to the industry savings, there are the additional benefits of improved crew safety and reduced threats of oil spill.

Safe, Efficient Shipping. The Physical Oceanographic Real-Time System (PORTS) integrates and delivers real-time environmental observations, nowcasts and near-term forecasts to maritime industry users in many of the nation’s major ports. Studies in three ports have shown a more than 50% decrease in ship groundings following the installation of a PORTS system. Quantifiable benefit from Columbia River PORTS data is about $7.4 million/year.5

Return on Investment. An economic evaluation of the estimated value generated by NERACOOS data is about $6M/year based on a $2M investment, a 3-fold return on investment6

Tagging and Telemetry Data. The Great Lakes Observing System launched a system to track 1700 tagged fish to support fish population restoration actions. The U.S. IOOS office collaborated with the Tagging of Pacific Predators (TOPP) Program at Stanford University’s Hopkins Marine Station in a 6-month project for NOAA and Navy scientists to assess the value of data collected from open-ocean aquatic animal telemetry (animals wearing data collection and tracking devices known as “tags”). The tagged animals provide data from remote areas that are sampled poorly or not at all, and the scientists expressed enthusiasm about their value. The aquatic animal telemetry community is now developing a strategic plan to establish a national network under U.S. IOOS to make their data widely available to ocean scientists.

5 Kite-Powell, Dr. Hauke Kite-Powell; Estimating Economic Benefits from NOAA PORTS® Information: A Case Study of the Columbia River, June 2010, http://tidesandcurrents.noaa.gov/pub.html6 Kite-Powell, Dr. Hauke and Morrison, Dr. J. Ruairidh, Observing System Infrastructure and Economic Value, US IOOS summit white paper, July 2012


Integrating New Technologies. The United States has been working many years to transition its high frequency (HF) radar network to an operational system and has succeeded in moving from individual radars to clusters of radars to a comprehensive national network tied together through a common data architecture, set of practices, and a national plan.

Marine Industry Advances. As providers of observing system infrastructure, a number of U.S. companies are worldwide

leaders, especially in the areas of HF Radar, Gliders and marine instruments. Today the U.S.-produced SeaSonde® makes up 80% of all HF radars built worldwide. US companies make up 95% of the global market for ocean gliders, including the first surface glider powered by waves. And the U.S. is the largest manufacturer globally of marine instruments for the measurement of salinity, temperature, pressure, dissolved oxygen, and related oceanographic variables.

Open access to weather data has spawned many companies, and IOOS has begun to be a similar foundation for ocean related value-added companies. A private company (Surfline/Wavetrack, Inc) provides surf, wind and swell reports and seven-day forecasts to a wide array of private, commercial and government users worldwide, based on IOOS observing system and model outputs. A company in Florida (Roffer’s Ocean Fishing Forecasting Service, Inc) provides local fishing forecasts, and is both a user and provider of ocean information to US IOOS.

International Advances. In addition to the national success stories, U.S. IOOS has contributed to a many global milestones in observing and sharing ocean information through the international Global Ocean Observing System (GOOS) umbrella: With the development of profiling float technology under the World Ocean Circulation Experiment

(WOCE), Array for Real-time Geostrophic Oceanography (ARGO) reached its target of 3000 floats in 2005.

The Tropical Ocean-Atmosphere (TAO) array has expanded to the TAO-TRITON (Triangle Trans-Ocean Buoy Network) array, with a series of standard moorings, flux reference sites, CO2, and biochemistry sites in the Pacific, an expanded tropical ocean Prediction and Research Moored Array in the Atlantic (PIRATA), and the beginnings of a Research Moored Array for the African-Asian-Australian Monsoon Analysis and Prediction (RAMA) array in the tropical Indian Ocean.

A new observing program, the OCEAN Sustained Interdisciplinary Time series Environmental observation System (OceanSITES) includes approximately 100 moorings, considered sentinel sites, providing high quality air-sea flux data in key, unique, or strategic portions of the global ocean.7

The Global Ocean Data Assimilation Experiment (GODAE), the Array for Real-time Geostrophic Oceanography (ARGO) and the Global High Resolution Sea Surface Temperature (GHRSST) programs have shown that it is possible to reach global consensus on common standards.

With the emergence of web portals that can serve data to users in real-time, a number of Global Data centers such as GHRSST, ARGO, Global Ocean Surface Underway Data (GOSUD) and the Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM) Observing Platform Support Center have been established.

Global solutions to facilitate the sharing of biodiversity data have emerged, including the Global Biodiversity Information Facility (GBIF) and the International Ocean Biogeographic Information System (OBIS). The associated regional nodes, (e.g. OBIS-USA) and focused taxonomic nodes (e.g. OBIS-Seamap) have developed worldwide infrastructure to publish and share their data.8

7 Busalacchi, A., Celebrating a Decade of Progress and Preparing for the Future: Ocean Information for Research and Application. In Proceedings of OceanOBS’09; Sustained Ocean Observations and Information for Society (Vol.1), Venice, Itlay,doi:10.5270/OceanObs09. pp 458Pouliquen, S;,Hankin, S.,Keeley, R., Blower, J.,Donlon,C.,Kozyr, A.,Guralnick, R., The Development of the Data System and Growth in Data Sharing. In Proceedings of OceanOBS’09; Sustained Ocean Observations and Information for Society (Vol.1), Venice, Itlay,doi:10.5270/OceanObs09. pp 31.


GOOS participation in the international Group on Earth Observations (GEO) has increased the focus on ocean observations. The GEO System of Systems (GEOSS) workplan for 2012-2016, recognizes their societal benefits in a section titled Blue Planet that emphasizes the need for sustainment, improved global coverage, data accuracy, and development of a global operational ocean forecasting network.

3. Assessments and Accomplishments

U.S. IOOS has evolved over the last decade to include a national program including: A robust U.S. contribution to global GOOS efforts Federal agencies that provide observations, data management, products and services to meet

their own missions, but in formats that contribute to the greater IOOS community A Regional observing network that connects IOOS to the local level A national U.S. IOOS Program Office that serves as the overall integration mechanism.

AssessmentAssessing a complex system such as IOOS is difficult, but we have measured our progress over the past decade using plans and recommendations from the Airlie House workshop of 2002, the First U.S. IOOS Development Plan of 2006, and the US IOOS Blueprint of 2010 (http://www.ioos.gov/about/governance/welcome.html). This resulted in both a quantitative and qualitative evaluation. The Airlie House report and the IOOS Development Plan laid out specific milestones for each of the Subsystems of IOOS. A detailed comparison of the state of the ocean observing enterprise between what we set out to do, the state in 2002 and the state in 2012 is contained in Appendix E. Table 3 summarizes IOOS progress.


Table 3. US IOOS Progress Past - 2002 Present – 2012

IOOS GlobalContribution to

GOOS

45% completed in 2004 62% completed

ObservingSubsystem

12 PORTS® operational nationwide 175 National Water Level Observation

Network (NWLON) (none with real-time data delivery or meteorological sensors)

60 NDBC buoys 89 stations measuring directional waves

21 PORTS® operational nationwide 210 NWLON (all real-time; 181 with meteoro-

logical sensors) 103 NDBC buoys A National Waves Plan has been completed.

Data Management and

CommunicationsSubsystem

Disparate and uncoordinated standards, protocols, and formats

No coherent data management strategy Call for National Standards Ocean Biogeographic Information System

(OBIS) in the pilot stage with the first set of OBIS nodes funded by the National Oceanographic Partnership Program (NOPP) in the mid-2000.

Quality Assurance of Real Time Oceanographic Data (QARTOD) was established in 2003 with increased development of quality control.

DMAC Steering Team was established by Ocean.US in the Spring 2002 and continues to function today

Data Management and Communications System Architect in the U.S. IOOS Program Office

Creation of Data Integration Framework (DIF) Master Project Plan

Eleven Regional Associations Data Assembly Centers in the Regional Coastal Ocean Observ-ing System (RCOOS)

OBIS

Modeling and Analysis

Subsystem

No coordinated effort on: improving, developing, testing and validat-

ing operational models; producing accurate estimates of current

states of marine systems, or developing assimilation techniques

US IOOS Coastal and Ocean Modeling Testbed endorsed by Federal agencies

Regional models and products are now serving stakeholder needs

While capabilities exists in the community, fund-ing has not yet been applied towards optimizing the observing subsystem

Research and Development

Less than 15 High Frequency radar nodes for coastal current mapping nationwide.

Limited Glider projects for water column profiling

Call for In situ sensors for real-time measurements and data transmission of key biological and chemical vari-ables

Call for coupled physical-ecosystem National Oceanographic Partnership Program (NOPP) and NASA awards

130 High Frequency Radars and a national data management; assimilated operationally by Coast Guard and NOAA

Navy using gliders operationally; 52 gliders in Regions; employed by OOI; National Glider As-set map and national Glider plan being devel-oped.

Partially operational Harmful Algal Blooms fore-casting system

Education and Outreach

Call to: Establish an IOOS Allied Education Com-

munity Develop an ocean literate society based on

US IOOS information Develop Professional certificate programs

NSF COSEE program in place A number of regions have developed lesson

plans using IOOS data for classrooms (http://www.ioos.gov/education/welcome.html)

MARACOOS has developed HF Radar and Glider technician certificate programs


This section on satellite observations will be modified to address IOOS requirements along with data from other sensors measuring the same ocean variable. A priority of IOOS is the sustainment and improvement of satellite observations. Figure 1 shows that through strong international collaboration we have raised the awareness of gaps in the adequacy of the satellite observations, but the overall health of our ocean-related remote sensing capability is marginal. Efforts in this area have focused on extending and improving observing capabilities that were already in place during the 1990s, and maintaining those that have been were launched subsequently.

Figure 1: Satellite Observation Status

In June 2011 the Aquarius satellite (a collaboration between NASA and the Space Agency of Argentina/Comisión Nacional de Actividades Espaciales) was launched as a focused effort to measure Sea Surface Salinity, and will provide the global view of salinity variability needed for climate studies. The Suomi National Polar-orbiting Partnership, launched in October 2011, collects and distributes remotely-sensed land, ocean, and atmospheric data to the meteorological and global climate change communities. It will provide atmospheric and sea surface temperatures, humidity sounding, land and ocean biological productivity, and cloud and aerosol properties. The U.S. IOOS Program Office produced the 2012 IOOS Blueprint Version 1.0, which can be found at http://www.ioos.gov/about/governance/welcome.html The Blueprint’s


http://www.ioos.gov/about/governance/welcome.html

architectural framework does not prescribe specific system or technical solutions, infrastructure/facility material solutions, detailed business process steps, funding mechanisms or an organizational/management structure for the U.S. IOOS Program Office. It does employ an architectural framework for describing a full capability (FC) for IOOS, including partnership roles and responsibilities and implementation requirements. An architectural framework provides a structured approach for organizing and describing discrete activities and components of IOOS that can be uniformly and repeatably applied to all IOOS-related capabilities and participants. The architectural guidance and documentation in the Blueprint are used to:

• Establish initial requirements• Describe what needs to be accomplished, who executes it, and in what order• Provide functional descriptions, including working relationships among IOOS components

Core Functional AnalysisThe U.S. IOOS Program Office conducted an assessment of the Federal Agencies and RAs that are part of IOOS to determine which functions and activities are currently being performed by which IOOS Federal and non-Federal partners, and which activities remain to be developed. The Blueprint identifies core functional areas (CFA) that describe the U.S. IOOS Program management products and services. The CFAs were derived from stated or implied requirements in the ICOOSA and the IOOS Development Plan. CFAs are the minimum capabilities required for an effective IOOS and represent, at a high level, the contribution required of U.S. IOOS to produce a cohesive suite of data, information, products, and services related to our coastal waters, Great Lakes, and oceans. Each core functional activity has subordinate activities.

The U.S. IOOS Program Office used a system of capability readiness symbols (Figure 2), to represent the assessment of the ability of IOOS to perform required activities at a given point in time. The symbols do not convey the effectiveness or efficiency with which the activity is conducted, but focus on the readiness to perform an activity. Figure 2. Definitions of the Readiness symbols

Pre-Developmental. New partner is recognized as a member of U.S. IOOS and has established preliminary partnership development plans, to include assigning resources and tools.

Developmental. Partner has begun development process leading to Initial Capability (IC) for assigned roles.

Minimum Essential Functionality. Partner has achieved IC—accom-plished minimum critical functions associated with IC for assigned role(s).

Significant Functionality. Partner as begun development process leading to Full Capability (FC) for assigned role(s).

Full Functionality. Partner has achieved FC—accomplished critical functions associated with FC for assigned role(s).

Figure 3 shows results of the analysis of readiness of the Federal Agencies.


What this tells us is there are opportunities to pursue growth in IOOS capability through partner contributions. For example:

Observing Subsystem: Pursue partnership agreement opportunities with USACE and Navy/ONR in core functions within the Observing Systems subsystem in the area of optimization studies and asset management.DMAC Subsystem: Pursue partnership agreement opportunities with USACE, USGS, and NOAA in core functions within the DMAC subsystem such as utility services development and configuration control. Modeling & Analysis Subsystem: Pursue partnership agreement opportunities with USACE and USGS in assessment and management of sponsored models. Research & Development: Pursue partnership agreement opportunities with USACE, USGS, NOAA, Navy/ONR, and BOEM in core functions within the R&D subsystem for requirements determination, coordinated pilots.


Figure 4 presents the assessment of readiness of the Regional Association Assessments.

From this we assess that Regional Associations are active in all of the subsystems, and collectively display a solid foundation of IOOS capability. Overall, while the RAs have capability in some of the sub-activities in each subsystem, no region has “full capability” in any subsystem.

The GOOS system, to which the US IOOS global component provides 50% of the funding, has determined an initial end state. Figure 5 depicts the progress during the past decade toward these global goals of the U.S. IOOS program.

Figure 5 Global Ocean Components


This same identification of an end state of the subsystems does not exist for the coastal component of IOOS. However, the U.S. IOOS Assessment, conducted by the U.S. IOOS Program Office, evaluated IOOS capability as it existed in 2010 among U.S. IOOS partners for the coastal component. Future assessments of progress will be based upon the Summit Vision and associated implementation guidance. Below are the results from the Assessment regarding assets that contribute to the Observing, DMAC, and Modeling and Analysis subsystems.

Observing SubsystemFigure 6 depicts the observing programs and assets that contribute to IOOS, as part of the Blueprint assessment. Next steps should focus on identifying how they fit together and where gaps in capability exist against requirements.

Figure 6

Some federal programs do not have sustained programs or systems, but still provide valuable contributions to the Observing Subsystem. The Bureau of Ocean Energy Management (BOEM) has played an important role in regard to increasing observing assets by required issuing a Notice


to Lessees (NTL) requiring oil & gas platforms to collect and transmit current data in near real time and providing it as non-proprietary data transmission into the Federal IOOS data stream. Through their ocean studies program, in anticipation of drilling in the Arctic, BOEM has been funding University of Alaska to provide HF Radar, drifters and gliders for data collection there. The RAs have the responsibility not only for deploying observing assets but also providing access to ocean, coastal and Great Lakes data collected by State, Local, Tribal governments, academia, industry and non-governmental organizations. The RAs provided an initial inventory of assets, stood up Regional Data Assembly Centers (DACs), and completed Regional Build Out Plans. Based on many years of interaction with users in their regions and nationwide, the RAs identified priority user needs in four primary categories: marine operations; coastal, beach and near shore hazards; ecosystems, including fisheries, and water quality; and long-term trends in ocean and Great Lakes conditions. These broad themes and specific user needs associated with them are The process for developing the Regional Build Out Plans began with each individual RAs identifying user needs, products and required assets for their own region. This information was then synthesized to identify common elements across the nation as well as unique regional circumstances. A draft, national synthesis document, http://www.usnfra.org/buildout.html, defines 29 common products and services that should be provided in all the regions after a 10-year implementation period. Figure 7 represents the assessment of the observing requirements laid out in the Regional Build Out Plans.


http://www.usnfra.org/buildout.html

Figure 7. Assessment of Requirements as per the Regional Build Out Plans

A foundation for all IOOS activities and products is effective, accurate, precise and reliable in situ and remote sensing instruments to quantify key parameters and to document environmental conditions and changes over time. The Alliance for Coastal Technologies (ACT) was developed, in large part, to fulfill one aspect of these IOOS technology requirements, by providing an understanding of sensor performance and data quality, while facilitating the maturation of novel technologies. Since 2004, ACT has evaluated 49 sensors from 25 international companies; overall, ACT has conducted 235 tests of instrument performance in the laboratory and in the field, under a wide range of environmental conditions and in different deployment applications. These Technology Evaluations have helped manufacturers improve their technologies and users make informed technology choices. The online Technology Information Clearinghouse now connects users with over 300 companies and nearly 4,000 commercial instruments.

Data Management & Communication Subsystem DMAC is the central mechanism for integrating all IOOS data sources into compatible formats.. Figure 8 represents the Federal contribution to DMAC.


Figure 8 Federal Contributions to the DMAC

At the Global level individual programs such as ARGO and OceanSITES have global data assembly centers. In addition to the efforts of the US IOOS Program Office to provide a national consistent data management picture of IOOS, the data must also be provided in formats that serve communities. For example, the World Meteorological Organization (WMO) and national meteorological services rely on the Global Telecommunications System (GTS) for ocean data dissemination to support atmospheric modeling, and the IOOS Data Assembly Center at the NWS’s National Data Buoy Center provides this service. Since 2002 the number of ocean data records being sent to the GTS has risen from less than 500,000 in 2003 to over 11 million in 2011. At the Regional level, each of the RAs has stood up Data Assembly Centers (DACs) which have significantly increased user access to ocean data. For example Central and Northern California (CeNCOOS) provides real-time ocean and coastal information from 183 assets and 23 partners while the Northwest Association of Networked Ocean Observing Systems (NANOOS) provides information from 167 assets and 25 partners.

Modeling and Analysis Subsystem

NOAA’s National Ocean Service (NOS) applies hydrodynamic models for the development, transition and implementation of Operational Forecast Systems (OFS) in U.S. estuaries, ports,


lakes and the coastal ocean. These models and systems have applications in the support of safe and efficient marine navigation and emergency response as well as marine geospatial and ecological applications on synoptic time scales (hours to several days). There are currently thirteen water bodies in which OFSs are functioning and new OFSs are under development. Once tested, fully evaluated, and deemed accurate by NOS standards, experimental forecast systems are transitioned into the operational environment.

A new strategy of transitioning from individual port or estuarine models to a regional modeling approach is being developed and implemented to enhance the efficiency of development and operations. The first NOS regional model was recently implemented for the northern Gulf of Mexico and includes a high resolution model of the continental shelf as well as higher resolution grids (nests) in up to six ports in Texas, Louisiana, Mississippi and Alabama. A similar approach is planned for the U.S. West and East Coasts. Current OFS coverage is ~30% of the coastal continental U.S.

In 2010, U.S. IOOS established the Coastal and Ocean Modeling Testbed (COMT) to accelerate the transition of scientific and technical advances from the coastal and ocean modeling research community to improve certain operational ocean products and services. Initially addressing chronic issues of high relevance in the Atlantic and Gulf regions such as flooding from storm surge and seasonal depletion of oxygen in shallow waters, this project has established a robust infrastructure to facilitate model assessment, and detailed scientific investigation of both model output and data. Through the COMT, methods will also be explored for effectively delivering model results to regional centers, scientists, and managers relying on U.S. IOOS. Results from phase I of that effort include:

• Development of skill metrics for specific issues of societal importance;• Development of standards, web services and standards-based tools that work across a

variety of different model types and conventions, enabling interoperability and software reuse by following IOOS DMAC principles.

• Improvements to all models through comparisons with others.

For example, the Estuarine Hypoxia team reported that the CHESROMS model realized a 40% overall reduction in RMS difference between predicted and observed bottom dissolved oxygen concentration due to improvements identified during the Testbed project;

Research and DevelopmentA major development is the funding of the National Science Foundation’s (NSF) Ocean Observatories Initiative (OOI), a long-term program to provide 25-30 years of sustained ocean measurements to study climate variability, ocean circulation and ecosystem dynamics, air-sea exchange, seafloor processes, and tectonic plate-scale geodynamics. The OOI will enable powerful new scientific approaches for exploring the complexities of Earth/ocean/atmosphere interactions, thereby accelerating progress toward the goal of understanding, predicting, and managing our ocean environment. The OOI is expected to foster new discoveries that will move ocean research in unforeseen new directions.


4. Introspection Significant progress has been made in delivering the promise of US IOOS in the following areas:

• Setting up the national framework for ocean observing and providing the mechanism for the integration of regional observations from non-Federal sources

• Moved the U.S. IOOS enterprise from planning to implementation• Adding observing capability • Integrating data, which has significantly increased access to ocean, coastal and Great

Lakes information• Initiating An ocean modeling capacity based on community modeling • Fostering Industries which lead the lead the world in ocean observing technology• NSF’s Oceans Observatories Initiative (OOI) delivering a significant boost to Research

and Development.

But both external and internal factors have inhibited our progress. This Summit presents an opportunity to reflect on those challenges and establish a realistic vision for moving forward. We note first that the fiscal environment during the past decade did not lend itself to large infusions of resources for IOOS, and the present budget trend is level at best. We have also been impacted by internal factors over which we have some influence, and the list below provides representative examples of those: The ICOOS Act provides a comprehensive definition of US IOOS that includes contributions

by all civilian Federal Agencies, but it is not clear that this definition is fully embraced in a budgetary or staffing sense by those agencies.

The US IOOS Program office is a good start on an interagency office but it is not truly an inter-agency Program Office funded and enabled (with inter-agency authority? Influence?) to implement national IOOS plans.

A consensus among stakeholders on IOOS priority goals has yet to be achieved. IOOS proponents have failed to develop a consensus view as to what is most urgent, what can be done now, what can wait, what has large payoff in the near-term.

A leadership team of committed people in key positions inside and outside the federal government has yet to develop.

Although there have been many attempts to quantify economic costs and benefits of IOOS, the results have not been compelling to date, in part because many benefits are for the public good and are not established in the marketplace.

The ocean research community has yet to adequately recognize the value of IOOS to the research enterprise while, ironically, the proponents of IOOS are still perceived to champion an academic/researcher focus on science questions instead the potential economic benefits of IOOS.

There are many examples of Regional Association successes and we have demonstrated that the enterprise has the ability to maintain a national network (e.g, Hf Radar) and respond to crises, but we are generally perceived as pursuing too many priorities and therefore taking too long to make progress.

Interdependencies among Federal, State, Local, Academia and NGO stakeholders are expressly encouraged. This is a valuable position, but its adoption presents a very complex business model. If the Federal funding stream is decreased, we may lose exponential capability because other partners are not currently positioned to step up to major funding.


Chapter Three: User Engagement and Requirements

1. IntroductionThe frameworks of GOOS and GEOSS, IOOS® deliver a number of key benefits to users. Through federation of common requirements IOOS permits more effective and timely delivery to existing users of marine data and information. Through better integration of their needs, and the use of common data infrastructure, analyses and models, IOOS enables improvements to existing uses through better quality core data and information. IOOS also enables a range of new uses by virtue of delivering better understanding and prediction of open ocean, coastal and great lakes processes.

At the Airlie House Workshop in 2002, the needs of users were not well understood. As such this meeting concentrated on formulating a scientific, technical and governance structure for a US IOOS. Later, the nascent IOOS structure that emerged from this vision moved towards a focus on delivery of core data and information required to meet a specific set of uses.

Over the coming decade, IOOS must move towards delivering a comprehensive range of core data and information needed to fully support the needs of all users and able to respond quickly and effectively to emerging needs. To do so IOOS must develop a clear understanding of the IOOS enterprise stakeholders and secure their continuous engagement as beneficiaries and advocates.

Stakeholders in planning, construction, operation and use of IOOS comprise three main categories: Providers of observing system infrastructure and outputs; intermediate users who take U.S. IOOS data or information and tailor it for a specific end-use; and end-users whose activities or businesses benefit from U.S. IOOS data and information.

Providers of observing system infrastructure include manufacturers of sensors, instruments and platforms; operators who deploy, run, and maintain the in situ observing stations; those building, launching and operating satellite systems; those providing the cyber infrastructure that interconnects the U.S. IOOS components; and organizations that develop and maintain the data management systems, software tools and models used to turn U.S. IOOS data into useful information. Intermediate users are organizations that add value to U.S. IOOS outputs tailoring them for specific end-uses. End-users are the ultimate beneficiaries of U.S. IOOS. They use value-added products generated in whole or in part from U.S. IOOS data and information as an input to their activities or businesses to derive specific scientific, societal or business benefits.

End-users of U.S. IOOS data and information fall into four main types:

Operational end-users who make use of ocean data and information to support decision-making related to safety, economic efficiency and protection of the environment (mariners, commercial fishermen, and others needing access to data most usually in near real time for business decision-making)

Science end-users who undertake research activities that rely in whole or in part on sustained measurement and observation of the oceans.


Policy end-users who require sustained ocean data and information to support policy formulation, monitoring of policy compliance, and assessment of policy effectiveness;

Public end-users who are primarily interested in accessing products that synthesize or analyze data to provide specific information relevant to their leisure activities (recreational boaters, divers, fishermen, beachgoers, surfers).

The providers of data, products, and information are actually the first users with requirements for those data, products, and information, because the data collection and product development is done to meet specific mandates and responsibilities of those user/providers. It was these providers-users whose requirements informed the 2002 Airlie House Workshop, and whose goals did not include explicit identification of other users and their requirements at that time.

What did we know about user requirements 10 years ago and how does it compare to today? A decade ago, the community of people interested in the international Global Ocean Observing System had accepted the seven societal goals determined through the discussions and negotiations of nations formulating the GOOS program. In 2002, the Airlie House planning participants focused on identifying and prioritizing the core variables required to address those seven societal goals. They also recognized the need to have regional organizations that would gather information from the regional stakeholders on the region-specific needs—the birth of the concept of the Regional Associations.

In the ensuing ten years, the Regional Associations have been established, and they have engaged with users in many different ways. The past decade of engagement with users of all types has resulted in a much improved and stronger understanding of the wide range of users, their interests, and the types of data, products, and information they may need to improve their decision-making both for their communities and themselves. But the engagement needs to go further to have truly integrated users that are also providers and advocates for U.S. IOOS.

Many users are beginning to see that the mature U.S. IOOS can deliver broad and multiple benefits to them by:

making use of observations, measurements, and model outputs in a structured way to generate gridded data sets and other integrated products needed for decision-making,

filling gaps in observations both as to type of variable and location, insure the continuity of datasets, and delivering data products of known quality in machine-to-machine or other user-selected

formats.

Yet the U.S. IOOS is not mature, but still in its adolescence. Over the next decade, the engagement process must continue unabated to ensure that new providers continue to be entrained into the U.S. IOOS; the engagement with users continues to provide the information on changing requirements as the state of the oceans and Great Lakes change; and the information on providers, users, and requirements continues to be consolidated and used to inform the decisions on the development of the U.S. IOOS to meet user requirements. In all these engagement activities, the Regional Associations will remain at the forefront of the effort to evolve the coastal module of U.S. IOOS.


2. User Engagement and Requirements

Significant progress has been made in the last decade by the U.S. IOOS enterprise and global ocean observing communities in defining user requirements. These advances are accompanied by an increase in scientific understanding, sensing capability, and information technology, and add complexity to the task of maintaining an effective user engagement system, in which defining requirements are but one component.

Hallmarks of Successful User Engagement Successfully defining user requirements is an iterative process characterized by mutual understanding, commitment, and trust between the user and provider. The "corporate culture" of the U.S. IOOS must be one where user engagement is a top priority, and these efforts must be funded at a significant enough level to make a difference.

At the level of the Global Module of U.S. IOOS, engagement is usually conducted within the spheres of federal agencies and their consultants and contractors, with some reasonable level of funding supporting the efforts due to the international characteristic of the engagement.

At the level of the Coastal component, the U.S. IOOS Program Office and the agencies of the Interagency Ocean Observing Committee are in effect serving two masters. The contributions by the Federal agencies are assets supporting their own missions, but these need to be better integrated into the U.S. IOOS—both to more fully represent all the user groups and to improve entrainment of the data, products, and information from these agencies into the System of Systems.

The U.S. IOOS RAs operate on the local, regional, and even national scales of user interfaces. The RAs have devoted significant resources, including voluntary efforts by partners, to user engagement. As a result, the RAs have established strong relationships with many users and have worked to define the requirements of those users over the last decade. This progress, however, needs improvement and an infusion of additional resources if we are to substantially increase the value and support for the U.S. IOOS infrastructure.

The level of engagement of users, in the way originally envisioned for the U.S. IOOS enterprise, has ranged from excellent to mediocre. A few examples are given below.

Example 1. Turning Users into Data ProvidersThere is always a shortage of in-situ data for the assimilation and validation of coastal ocean circulation models. In the Northeast Region, the Environmental Monitors on Lobster Traps (see http://emolt.org) project addressed that problem by working with lobstermen to place sensors on their traps. Start-up funds were provided by NOAA’s Northeast Consortium, and maintaining the program requires only low-cost replacement probes approximately every five years and a few months of personnel time each year to process the data. There is now more than a decade of hourly bottom temperatures at dozens of fixed locations as a result of this program. Salinity sensors, bottom-current meters, acoustic listening devices, tide-gauges, and underwater cameras that provide a time series of biological activity have also been deployed on the traps. The fishermen also assist with deployment and recovery of student-built satellite-tracked drifters in order to help document surface current flow (see http://www.nefsc.noaa.gov/drifter). In addition to providing data for coastal ocean circulation models, the project has engaged many fishermen


in the process of monitoring their environment. These fishermen have the biggest stake in preserving our coastal marine resources, and are most knowledgeable of the local waters. This is an excellent example of developing a solution to a data deficiency, which resulted in engaging users by turning them into data providers.

Example 2. Research to Operations (R2O) Success Is Not Enough Results of a four-day test in July 2009 showed that when HF radar data were ingested into the US Coast Guard’s Search and Rescue system, the search area was decreased by 66%. The use of HF data is currently integrated in to Coast Guard Search and Rescue on a national level, but even this research-to-operations (R2O) success has not led to needed resources for expansion in the HF Radar assets distributed around the nation’s shorelines.

Example 3. Changing “corporate culture” Early in the formulation of the U.S. IOOS vision, the National Data Buoy Center (NDBC) took on the task of becoming the U.S. IOOS DAC collecting data from regional ocean observing systems, quality controlling the data, and distributing it in realtime via the Global Telecommunications System (GTS), and via their web site and netCDF files. As a result of the NDBC efforts, there are ~400 additional, non-federal observing stations in the coastal ocean and Great Lakes contributing to the federal data stream that goes out over the GTS (Figure 9), compared to the [need #] federal stations. The NDBC became engaged early-on in the U.S. IOOS vision as a user and a provider, committed to a substantial role in the IOOS data streams. This illustrates how a federal agency can change its "corporate culture" to entrain itself into the IOOS vision for the benefit of the nation.

Figure 9. Stations in the IOOS DAC operated by NDBC. Showing stations at 2200 CT on 8/26/12 (available at <http://www.ndbc.noaa.gov/obs.shtml> by selecting "IOOS Partners" in the Program Filter).


http://www.ndbc.noaa.gov/obs.shtml

Example 4. Data is not enough; it must be integrated. The Gulf of Maine buoy array of NERACOOS has provided continuous oceanographic measurements for over a decade. Currently there are seven buoys in the array sited at coastal shelf depths ranging from 50 to 250 m and providing temperature measurements at 3-7 depths throughout the water column. Analysis of this time series shows statistically significant warming trends at all depths for all locations, providing the first depth-resolved rates of temperature variability for the U.S. East Coast from continuous data. Ecosystem data are lacking, however, so there is no telling what impact this warming condition is having on the ecosystem. The impact of data is limited without human resources funded to analyze it and push results to broader user groups. User engagement is successful when the data are integrated in new ways to provide new understandings or new information for decision-making.

Example 5. Catastrophes radically change users requirements Sudden catastrophic events, such as Hurricane Katrina and the 2011 Deepwater Horizon oil spill, can have profound and sudden impacts on user requirements. Twice in just five years, the GCOOS-RA efforts were altered from a steady pace of engagement, entrainment and building solid commitments with users and providers, to an on-demand, urgency-driven engagement process with myriad new stakeholders. Ongoing projects, such as the development of a HAB Integrated Observing System, were postponed in order to deal with the emergency situations. Engagement personnel, many of whom were volunteers facing their own major losses associated with these events, were stretched thin, and the dramatic changes in stakeholder needs still reverberates in the engagement process today. Both of these events imposed a prioritization scheme on a response and monitoring system that had no mechanism for establishing priorities, which emphasizes how vital an effective prioritization process can be. Other changes in the environment and climate, such as increases in hurricane intensity, habitat losses from sea level rise, new invasive species, and increases in HABs will also impact user needs for data, products and information. It is imperative that the system be designed to recognize and response quickly to changing user needs.

User Engagement To understand user requirements with the specificity needed to transition from the research stage to operations, users and providers must be fully engaged. Successful user engagement is an iterative process, with eight steps presented below. They emphasize the resources necessary to generate user pull, which is largely lacking in the current U.S. IOOS infrastructure.

1. Identify the users. This seemingly straightforward step has been a major undertaking. Considerable progress has been made over the last decade to identify and build relationships with the users both of a nascent U.S. IOOS and a mature U.S. IOOS.

2. Prioritize the users and/or the products. Existing and potential users of U.S. IOOS are extensive, which follows from U.S. IOOS having a purposefully broad scope and impact. However, limited resources require that we prioritize who we are going to serve and/or what the system will serve, in terms of products or services.

3. Define user requirements. Defining user requirements is an iterative step that can only be executed if adequate human resources are committed to the process. Each user's decision


processes and operational needs must be fully understood Users requirements also extend to data access and dissemination, and are not restricted to just the data.

4. Develop Solutions. This is the iterative development stage marked by partnering of the RAs and IOOC agencies with private enterprise, non-governmental organizations, and/or local, tribal, state, and federal agency partners. A key to success in this step is keeping the user engaged and understanding that several options, iterations, or versions will likely be necessary before users are satisfied. Additionally, since this process can take months and years, user requirements will evolve requiring adjustment to solutions.

5. Conduct Outreach. In the private sector, this step is called marketing. Products will not be used if users are not aware and interested in trying them. This is the step that is most often cut from public sector development programs. It is a highly important step to achieve, but requires infusion of human resources and funding to keep moving forward.

6. Assess and Maintain Products. Follow-up assessments are required to ensure the data, product, or service continues to meet the user's need. Maintenance is critical to keep the user groups, their requirements, and the associated human and other resources necessary to meet the requirements up-to-date with the changing states of the ocean and Great Lakes. When accounting for resource needs to meet requirements, the long-term cost of maintenance of the system must be included.

7. Provide Training. Training of the technicians, programmers, scientists, educators, and others who will be needed for a mature U.S. IOOS is required. This step in engagement is often overlooked and hence under-planned with needed advances in training capabilities being under-funded.

8. Enable Advocacy. Through outreach (step 5), the users will better understand what the U.S. IOOS enterprise is trying to accomplish as a whole and for them as a user group. This understanding, coupled with successful provision of data, products, and information needed by users will lead to user-initiated advocacy for the enterprise, effectively turning end users into U.S. IOOS advocates.

An obvious conclusion from this discussion is that significant, well-qualified human resources are necessary to maintain effective user engagement. The U.S. IOOS enterprise must recognize importance of this process, and support implementation of a user engagement infrastructure in order to successfully become the envisioned System of Systems delivering critical and unique products to diverse users.

User RequirementsAn exhaustive discussion of what is known of existing user requirements is beyond our scope. Today, as opposed to ten years ago, sources of information on users requirements are extensive:

U.S. IOOS Summit community white papers (For requirements associated with SAR, HABs, waves, offshore renewable energy, and ocean acidification, see Allen, Anderson, Bailey, Birkemeier, Hall, and Gledhill papers, respectively.)

Regional Associations' Ten Year Build Out Plans (See http://www.usnfra.org/buildout.html for a synthesis of user needs and 29 common products identified in the RA Plans, grouped by societal themes).


http://www.usnfra.org/buildout.html

National Operational Wave Observation Plan (March 2009), which includes plans for a surface-wave monitoring network to meet the maritime user community’s needs.

Plan to Meet the Nation’s Needs for Surface Current Mapping (September 2009), which delineates plans for a national network of high-frequency radar stations to support search-and-rescue efforts and oil-spill response, among other societal needs.

U.S. Integrated Ocean Observing System: A Blueprint for Full Capability Version 1.0 (November 2010), which “identifies, describes, and organizes the specific functional activities to be developed and executed by U.S. IOOS partners”. Additionally, the U.S. IOOS Office is developing a series of perspective papers, including one on user requirements and gap analysis.

Requirements for Global Implementation of the Strategic Plan for Coastal GOOS, Panel for Integrated Coastal Observation (PICO-I) (July 2012)

Systematic organization of the requirements from these and other sources is in progress and will begin to address some of this chapter’s key recommendations. The RAs have made an effort to begin the task of organizing the requirements, both for products and data, of four major user categories that tie into the seven societal goals: Marine Operations9 , Coastal Hazards10, Ecosystems, Fisheries, and Water Quality11, and Long-term Variability12. These requirements were summarized from the 10-year Build Out Plans of the 11 RAs, which in turn derived their requirements from their extensive engagement with their regional communities and user groups. Note that the RA engagement included the regional offices of many federal agencies.

DISCUSSION: THE JOB OF THE US IOOS PROGRAM OFFICE, THE REGIONAL ASSOCIATIONS, AND NFRA TO FOCUS ON A VIABLE PROCESS FOR COLLECTING, PRIORITIZING, AND ASSESSING PROGRESS AGAINST REGIONAL USER REQUIREMENTS, AND INTEGRATE THEM WITH NATIONAL AND GLOBAL REQUIREMENTS. ASSESSING ONGOING EFFORTS AND DEVELOPING A PLAN FOR DOING THIS SHOULD BE A SIGNIFICANT AREA OF FOCUS AT THE SUMMIT.

3. Current Challenges

Below we discuss the challenges associated with each of the user engagement steps just outlined. Many of these challenges are related to communication and coordination. How can the requirements of users and stakeholders be better documented and communicated to data providers and those developing the infrastructure of U.S. IOOS? How can the public and other potential users be made more aware of the data available through U.S. IOOS? How can different federal agencies, different countries and different RAs coordinate to meet the diverse array of user requirements? How can we prioritize activities to address user requirements? How can we ensure that users are properly engaged in the transition from research-to operations for observational data streams and models?

9 hyperlink to Table __ in RA Build-out Plan (BOP) Synthesis10 hyperlink to Table __ in BOP11 hyperlink to Table – in BOP12 hyperlink to Table __ in BOP


There are also technological, financial and ideological challenges involved with meeting user requirements. For example, many users want biochemical measurements, but the system has been primarily focused on physical measurements. Due to lack of resources, users are often asked to supply funds in order to see their requirements fulfilled, which alienates that user community. Lastly, there are ideological or cultural challenges involved with different communities working together: the research/academic and operational communities, the public, private and university sectors; different federal agencies and different countries. Each of these different entities or communities has a different attitude or perception on what user requirements are.

Challenge 1 . Identifying the users of U.S. IOOS

This challenge has been met, but the range of users that are and could be served by U.S. IOOS is so extensive it is difficult to know how to tackle serving them.

Challenge 2 . Ensuring different federal agencies, different countries and different RAs agree on priorities. There are cultural challenges associated with different communities working together, and each has a different attitude or perception on user requirements.

Setting priorities for an enterprise with the scope of U.S. IOOS is a daunting task. Cooperating can be difficult within different parts of a single federal agency, and even more so between different federal agencies. The current economy requires that choices be made about where money will be spent. The rules governing U.S. federal agency budget development present seemingly impossible obstacles to developing U.S. IOOS-wide priorities.

At the global scale, there is increasing recognition that the U.S. will have to rely on foreign sources of satellite data in the coming years to meet our requirements for environmental satellite data. The Committee on Earth Observation Satellites (CEOS13, part of GEO14) is coordinating environmental satellite observations of the Earth. With limited resources, by what process do we ensure the widest range of local, regional, national and global requirements is met?

The United States’ ocean observing community has never been more organized, collaborative and disciplined towards common national goals and objectives than it is now, but challenges remain at the interface of the various communities. Cultural differences can limit our effectiveness when dealing with operational users; for example, many federal agencies have operational needs that could be addressed by other U.S. IOOS partners. An improved mechanism is needed to make it easy for both those with data streams or other potential solutions and operational programs to engage with each other. Another example is the different value system between academia, which prioritizes publication and grantsmanship, and the operational community, which prioritizes meeting user requirements. Since the non-federal observing system is being implemented mostly through academic institutions, the academic value structure needs to be widely understood and integrated into IOOS planning.

Challenge 3 . Better document user requirements and better communicate them to U.S. IOOS. There is a mismatch now between many of the user needs and the technical capabilities of the observing system.

13 http://www.ceos.org/14 http://www.earthobservations.org/


It is a legislative mandate for U.S. IOOS to be based on the needs of users15, but documenting user needs is not straightforward. Which users should be included? How should their requirements be determined and prioritized? How should the requirements be distributed among providers? The Federal Agencies and the RAs play important roles in fostering user engagement and documenting user requirements.

The timing of engaging with end-users to try to understand their needs must also be considered. Requirements have a shelf life. If the resources are not available to act on requirements and develop solutions, then documenting them may have negative impacts: 1) raising expectations of users when nothing can be done; and 2) wasting time because the requirements may change and will have to be revisited when funding is available. These impacts can be ameliorated by developing and clearly communicating a prioritization schema, which will also support the process of securing funds. It must also be remembered that user requirements extend to the data dissemination process, and active communication between users and data providers is crucial to establish efficient, user-friendly data distribution systems.

User requirements will change with time and with changing technology, and the requirements documentation process must be able to accommodate this. This would be especially helpful during catastrophic events, which cause dramatic changes in requirements over short time periods, often without an increase in necessary resource. Different types of users have very different requirements. For example, an operational model has a very constrained set of parameters needed in a continuous near real-time stream, whereas the needs of the public are more episodic and often require interpretation (Is it safe to swim at the beach today?) rather than a data stream.

An organizational mechanism is needed to bring together user community needs with the expertise of the research communities to produce meaningful products as well as to shorten the life cycle of transitioning research to operations. The structure should encourage intermediate users, including those in the private sector who specialize in bridging between providers and users, to engage. And we need better mechanisms to foster private enterprise activity that can fill gaps in the current U.S. IOOS system.

The present system has been built largely around collecting and modeling physical oceanographic parameters, which is useful to users such as those involved in marine operations and search and rescue. However, a larger segment of the potential user community is interested in observing biological systems and the biogeochemical exposures that drive them. Some physical circulation products, such as larval dispersal models, have gained favor with the biological user community. There have even been efforts to incorporate biological measurements, such as fluorescence sensors to describe algal density, but these have been driven largely by a desire to leverage available technology rather than as direct responses to the highest priority user needs for biological data. The investment in sensor development and modeling necessary to optimize the observing system toward biological or chemical questions (such as what are the nutrient sources driving algal blooms, or predictive models of when the next bloom is likely to occur) are still lacking. Such investment towards products beyond the purely physical models will be required to serve the larger user community.

15 Airlie House report, 2002.43 DRAFT IOOS Summit Report: October 31, 2012

There is also a spatial mismatch between the observing system capabilities and many desired applications. The observing system has been built as an expansion of large scale global oceanographic assimilation models. These generally operate at kilometer scale resolution and the coastal shelf serves as a boundary condition. In contrast, many of the IOOS user needs are located close to shore and operate on much smaller spatial scales. For instance, the water quality user community is interested in how land-based sources are transported along the coast, even to the point of needing to examine longshore transport within the surf zone for beach water quality modeling. While the spatial resolution of the models continues to improve, and there are some nascent efforts to move the model's boundary conditions closer to shore, there is still much fundamental technical work to be done before many user community needs can be addressed.

Challenge 4. Ensure that users are properly engaged in the transition from research to operations for observational data streams and models.

The Research to Operations (R2O) transition process has always been difficult, earning it the nickname of the “Crossing the Valley of Death,” but it is a fundamental part of U.S. IOOS. U.S. IOOS can point to many examples of a strong “push” from research communities to operationalize their data products, but a lesser “pull” from the operations side. No organized process exists to foster a strong and consistent “pull” from the operational communities, but this is needed to improve R2O transition to the level needed for a successful IOOS. To ensure timely translation of research into operations, not only are substantial informatics systems required, but also a formal infrastructure for user-driven, product development.

The Regional Associations have significant experience in user-driven, product development approaches. (See http://www.usnfra.org/products.html for 71 RA created products.) The RAs often serve as the linchpin between data generators and data product developers and users in the region, including federal agency representatives in the region. Improvements are needed to shift current individual RA and other U.S. IOOS stakeholder collaborations from a cooperative approach (working together toward independent goals) to a more coordinated approach (working together toward common goals).

The governance structure for the product development process could include a number of supporting structures, including user councils, thematic product working groups, a stakeholder engagement council, and leveraged use of existing stakeholder networks. A partnership between the U.S. IOOS Program Office and NFRA could engage all IOOS agencies and RAs to populate and support a User Engagement Council, charged with defining and fostering a U.S. IOOS R2O strategy. Key members should include federal agencies, private industry and the RAs, and this Council should be coordinated with the existing U.S. IOOS Advisory Committee. This will result in new observing opportunities, invigorate the ongoing user network feedback loop, provide the foundation for the implementation of the U.S. IOOS RA 10-year Build Out Plans, and ultimately lead toward achieving the vision of U.S. IOOS.

Challenge 5. Ensure the public and other potential users are made more aware of the data available through U.S. IOOS.

The RA education and outreach specialists already work with many different types of stakeholders16. U.S. IOOS data have been utilized in developing innovative undergraduate curricula that allow students to be active participants in innovations and partake in the active 16 [Simoniello]


http://www.usnfra.org/products.html

exploration of the world’s oceans17. There must be more work and investment in building a community of informal education specialists who can promote the use of U.S. IOOS information to achieve ocean literacy. U.S. IOOS must utilize existing tools and facilitate the development of new strategies for virtual social structures that encourage communication and sharing of ideas across disciplines18. For outreach to the general public, data dissemination must move beyond web pages and take advantage of expanding media technologies, such as smart phone apps and twitter feeds, to make data and products more easily available to individuals.

NOAA’s Sea Grant extension services provide agents with ocean expertise who interact directly with specific stakeholder group types; the Sea Grant system should be used to improve stakeholder engagement within U.S. IOOS.

Additional resources for the existing NFRA Education and Outreach Council would allow for an increase in outreach activities to formal and informal educators, undergraduate and graduate level students, and the general public. The outreach efforts, which put understandable information into the hands of the public, is in many ways just as important as the DMAC subsystem that puts quality data into the hands of users.

Challenge 6 . Ensure that U.S. IOOS products continue to meet user needs.

Many ‘levels’ of products are available for U.S. IOOS stakeholders, ranging from minimally processed data to decision-support tools, and more could be added. The challenge is to build more robust assessment, maintenance and product updates into the U.S. IOOS structure. Currently, if these activities are undertaken they occur on a case-by-case basis.

Challenge 7 . Ensure that U.S. IOOS products are widely used.

Dedicated human resources are required to conduct meaningful outreach and training. NOAA’s Sea Grant extension services can serve as models for stakeholder engagement within U.S. IOOS. It is important to insure that data dissemination meets user requirements and is user-friendly.

Challenge 8 . Developing and maintaining advocacy.

Although U.S. IOOS is a line item in the NOAA budget, it is a largely unfunded federal mandate. Many naysayers continue to question the value of integration, believing that agency programs supported with agency-unique budgets and supporting requirements are adequate. This argument does not address the inefficiencies of the fragmented Federal approach, and fails to support U. S. IOOS as a national ocean enterprise which lies at the heart of U.S. IOOS’ ‘failure to thrive’. What is needed are users and requirements that can make a strong case for expanded funding and improved coordination enable an effective, integrated Federal backbone.

By meeting all the previously identified challenges, advocacy will develop naturally if the stakeholders and users are actively engaged and their requirements are being met. However, a proactive advocacy strategy that addresses federal agency, RA, private industry, and NGO roles and limitations is needed. There is often an awkward interaction between users and the observing community that is trying to develop the U.S. IOOS because the conversations mix discussions about technical needs with those of financial support. The observing community has an earnest desire to define and fill user needs, but often cannot, having inadequate funds to

17 [Glenn et al]18 [Thouroughgood et al.]


achieve the desired data stream, integrated product, or other informational assets. In this situation, the issue of finances may be brought into the conversation prematurely, before the observing community has created credibility for their products. Such interactions create a perception that the U.S. IOOS entity is more interested in obtaining money than in meeting user needs. At the other end of the interaction spectrum, there are many users that have come to rely on observing system products without providing financial or political support for the system. The observing system community is not adept at turning that supportive relationship into advocacy for continued or expanded funding.

4. DRAFT Recommendations

On User Engagement

Organize information about users, their requirements and available products into a “marketplace”.

Develop an “Action Agenda” for U.S. IOOS that prioritizes near-term investments and steps along the path to a fully operational system.

Devote a portion of each IOOC meeting agenda to resolving coordination issues delivered unfiltered and confidentially to the IOOC.

The IOOC agencies should provide recognition and/or rewards for partnerships across cultural interfaces.

U. S. IOOS should enable more systematic engagement with users by establishing a structure for this engagement that fosters efficiency.

U.S. IOOS needs to invest in the development of (1) the necessary biological and chemical sensors and (2) higher –resolution coastal models.

Organize existing U.S. IOOS user engagement efforts into an ad hoc User Engagement Council and hold a National Forum to define a Research to Operations (R2O) path for U.S. IOOS.

Charge the User Engagement Council with development of an Outreach Strategy as a component of the overall R2O path.

Provide a detailee with an education and outreach background to the U. S. IOOS Program Office to staff the User Engagement Council and ensure cooperation with ongoing Federal and RA education and outreach activities.

Require that product metrics be developed for all U.S. IOOS branded products

Provide marketing and training using the IOOS marketplace and User Engagement Council.

NFRA coordinate with private industry, the Consortium for Ocean Leadership and other stakeholders to develop an advocacy strategy.

NFRA, in coordination with private sector stakeholders in U.S. IOOS, coordinate training for advocates of U.S. IOOS with professional societies like AMS and MTS,

On User Requirements


Collect the user requirements, observational requirements and others in a methodical, repeatable way.

For High-Frequency (HF) radars:

Assimilate HF radar data into physical and ecological models to enhance model performance.

Integrate HF radar data into decision support tools for marine operations (e.g., search and rescue, oil spill response, and tsunami warnings), and incorporate HF radar surface currents data into PORTS® and the National Currents Program.

Proactively address the HF radar network health, balancing operations and maintenance (O&M) activities of existing radars with expansion of the network. Seek new methods for lowering the O&M for the HF radar network.

Develop a plan for the long-term stewardship of HF radar data to develop climate data records for use in climate science, adaptation, and mitigation strategies.

Enhance U.S. IOOS interagency and regional collaboration with the National Water Quality Monitoring Council to improve data integration and monitoring coordination to better meet local needs for timely water quality information and decision support.

Enhance the ability of U.S. IOOS to collect, deliver, and use biological data towards the goal of full integration by implementing the recommendations from the 2010 report Attaining an Operational Marine Biodiversity Observation Network (BON) Workshop. Initiate a multi-agency integrated marine BON demonstration project to pursue initial steps to advance sample processing, taxonomic identifications, data management, and training.

Develop a collaborative project designed to support ecosystem science and management requirements by demonstrating the utility of the Animal Telemetry Network (ATN) to fisheries and habitat management communities and advancing the recommendations from the March 2011 Toward a National Animal Telemetry Observing Network (ATN) Workshop Synthesis Report.

Specific recommendations on user requirements, from the Ocean & Coastal Build-out Plan are shown in Table 4 (see Chapter 4). This report is under development, and will be completed and released


Chapter Four: Observing System Capabilities -- Gap Assessment and Design

I. Introduction

This chapter examines the challenges, issues and opportunities in developing a comprehensive design of the U.S. Integrated Ocean Observing System. A clear, widely-endorsed vision for U.S. IOOS® and agreed requirements and priorities that flow from that vision, are prerequisites of a design for IOOS. Consistency of vision, priorities and requirements from global to local scales is a challenge. Priorities will vary regionally, and will require ongoing refinement, but should conform to the overarching vision. Identification of specific capabilities in each of the subsystem components of IOOS that are essential to satisfying the requirements of IOOS can provide common threads for design. This chapter assesses the progress and status of the U.S. IOOS enterprise in developing a comprehensive design, and highlights steps that need to be taken.

References to the development of the international GOOS program are included to ensure consistency across all scales and to identify strategies or pitfalls that may be applicable to U.S. IOOS efforts. Accurate assessment and prediction within the U.S. IOOS geographic area requires accurate information at its fluid offshore boundary and thus interoperability with the international GOOS efforts are needed. Similarly, input from terrestrial watersheds to the IOOS domain must be provided in an interoperable fashion if its influences are to be understood.

A comprehensive design is an important step towards detailed costing and implementation planning. It can be viewed as an opportunity to align interests and methodologies prior to significant expenditures. The design process will also naturally lead into discussion of implementation and appropriate roles and responsibilities for participants and should be a venue for refining these next steps. Design and gap analyses are needed for each of the U.S. IOOS Functional Subsystems: the Observing Subsystem (in-situ and remote sensed), the DMAC Subsystem, and the Modeling and Analysis, Modeling & Applications Subsystem.

The existing U.S. coastal ocean observing system was built with the support of a wide range of sponsors and users, and with applications as varied as safe navigation and beach water quality monitoring. Many platform locations and sensor types arose as “mission dependent”, uncoordinated collection of sensors that bears little or no resemblance to a carefully designed, multi-sensor, multi-user observing system. We need to examine the existing system of sensors and sensor platforms with a view to identifying opportunities for improvements -- from co-locating more sensors on existing platforms, or re-locating existing platforms based on scientific or operational need. The wise use of increasingly scarce resources will guide many of these decisions, but in all cases the assurance of meeting identified scientific and societal needs should be paramount. Herein lies an important but often misunderstood or unrecognized point – scientific and societal needs should be one and the same and should be adopted as such in the years ahead as a fundamental guiding principle of IOOS. The ocean sciences community understands the limitations of existing observation and prediction systems to deliver all of the required information at all locations. We employ models and data assimilation to fill the very


large gaps in our direct observations. Although we need to do more to understand the skill of these combined systems, we have seen their impact in providing real-time and near real-time information to users, addressing important societal goals. The scientific community in all sectors – public, private, and academic – must act in a coordinated fashion to improve and expand on these successes.

2. Overarching Issues

Unifying a design across the breadth of scales of U.S. IOOS responsibility relies on commonalities in vision at differing scales. The NOAA IOOS Program Strategic Plan (NOAA, 2007) provides a vision for the governance, design and implementation of IOOS. It identifies an initial set of priorities and core variables that support them. At global scales the OceanObs’09 Conference resulted in a revised vision for GOOS and a framework (Task Team, 2012) for establishing requirements for Essential Ocean Variables (EOVs). Both of these approaches are similar to that of Ocean.US in its initial depiction of IOOS (Airlie House Workshop report) and its articulation of core variables, and the subsequent expansion of the list of core variables to better capture the interdisciplinary observations needed to address priority topics in the IOOS Blueprint. The recent build-out plan synthesis developed by the IOOS Regional Associations also resulted in a revised list of core variables.

Table 4. Regional Association Build-Out Plan list of variables.

Variable May be measured from manned in situ platforms

May be measured from unmanned in situ platforms

May be measured remotely


Acidity (pH) x xAir temperature+ x x xBarometric pressure+ x xBathymetry x x xBottom character x x xColored dissolved organic matter xContaminants x xDissolved nutrients x xDissolved organic matter+ xDissolved oxygen x xExtent and condition of benthic habitats+ x xFish abundance x ?Fish species x ?Freshwater flows+ xHeat flux x x xHumidity+ x x xIce distribution x xOcean color x x xOptical properties x x xPartial pressure of carbon dioxide (pCO2) x xPathogens x x1

Phytoplankton species, and abundance+ x x ?Precipitation+ x x xPressure+ xSalinity x x xSea surface height+ x xSea turtles and marine mammals+ x xSound+ x xStream flow xSubsurface currents+ x xSurface currents x xSurface waves x x xTemperature x x xTotal suspended matter x xTurbidity+ x x xVisibility+ x xWater level x xWind speed and direction x x xZooplankton abundance x xZooplankton species x ?

DISCUSSION: HOW DOES THIS LIST DIFFER, WHAT SHOULD BE DONE ABOUT THE DIFFERENCES? – WHAT’S THE PROCESS??] The similarity of approaches suggests that given an alignment of priorities, a common set of variables can be identified for which requirements can be developed that span the full range of scales the U.S. IOOS aspires to cover.


The Global Climate Observing System (GCOS) and GOOS have developed detailed design and implementation plans and these continue to be refined and updated. The internationally agreed plan for the initial global ocean observing system was revised in 2010 and is described in GCOS (193)/GOOS(184), and the most recent summary for an ecosystem based management approach to the coastal component of the global system is described in GOOS (193). More detail on needed sustained satellite observing activities was most recently updated in 2011 and is given in GCOS (154). Progress against the initial global ocean plan was most recently described in 2009 in GCOS (128). Both the global ocean and global coastal system plans advocate for significant national activities along the coasts and in coastal waters. GOOS (193) invites, in particular, national participation in a set of Global Coastal Network activities (see section 5.4). A major issue for all these plans is working to agreed common standards and to timely free and open observation exchange.

Identification of a limited set of variables that are to be observed, modeled, and used in the development of information products and deliverables that directly address the priorities has been found to streamline the requirements process. GCOS(193) provides the list of GCOS Essential Climate Variables (ECVs) for the ocean (and atmospheric and terrestrial) domain. GOOS(193) offers a set of essential ocean variables (Table 14) for the Global Coastal Network. For state estimation and prediction, requirements will specify the spatial resolution, observation frequency and duration, accuracy, and speed of distribution needed. The requirements may then be met based solely on observations, or may be met through data synthesis which may use data assimilative modeling. Products derived from the variables will impose certain analysis and processing requirements. Information management will be required to support the variables through standards development and exchange protocols that facilitate aggregation from all observing platforms and with modeling and product development systems. It should be expected that requirements will change over time. The space/time/accuracy requirements for the ocean ECVs of GCOS/GOOS are revised routinely and are listed in the WMO Observing Requirements Data Base (http://www.wmo-sat.info/db/). The recent GOOS (193) report is a noteworthy example of a process that can be followed to translate priorities into observing system requirements and the use of these requirements in design.

Ongoing challenges of uniting ocean observing efforts into an integrated system of systems is the patchwork of existing systems of limited interoperability and the limited financial support available for integration activities and new observing component programs. For example, the GOOS initial global physical and carbon climate observing system remains only partially deployed due to lack of national commitments to sustained investment. The governance for coastal IOOS has matured significantly since the Airlie House Workshop, but support for implementation has largely been absent. Regional associations have formed and demonstrated the utility of integrating available observing system components but have lacked the resources to implement systems that can fully address the set of initial priorities. IOOS stands at a crossroad of development – if it is to meet the expectations for the coming decade, significant growth of the system will be needed. At issue is how can growth be undertaken in the most efficient and complementary fashion to existing efforts? And is there the political will for investment?

Observation and prediction of some variables are already reasonably advanced, such as water temperature and sea level, whereas others, such as species-specific harmful algal bloom toxins,


http://www.wmo-sat.info/db/

are much less so. A balance of investment in mature observing systems components and in pilot programs to demonstrate new capabilities is needed to ensure that an interdisciplinary system is developed and sustained.

After agreement on requirements, a census of the present state of observing system components is a necessary starting point for gap assessment. For federal agency participants in IOOS the identification of programs and assets that are considered part of IOOS has begun with the U.S. IOOS Blueprint for Full Capability (IOOS Project Office CWP on gap assessment). This critical step requires self-identification of relevant programs by agencies, and presumably a commitment to sustain the contribution to IOOS. Regional IOOS has recently completed a build-out plan that includes a census of most of the non-federal US contributions that exist at present. Within GOOS the 2009 summary of progress lists the initial in-situ global system to be about 60% implemented, with year to year variation in the extent of deployment of many of its subsystems; little progress in overall in –situ system implementation has been achieved over the past several years. The satellite component has been well implemented. Both the in-situ and satellite systems lack national commitments to sustain the present levels.

Gap assessment is the comparison of requirements for the observing system with its present state to establish what is missing and must therefore be added to the observing system to improve its functionality. Statement of requirements for the observing system derived from a synthesis of societal and scientific priorities, likely in the form of resolution and accuracy specifications of essential or core variables, is challenging because of the necessary translation from a set of specific objectives into observing system component needs. An agreed upon framework for the observing system and its components, or design, facilitates this task by providing a finite number of ways to implement the system. The high-level design of U.S. IOOS -- of 3 major subsystems -- has been in place for a decade, but a more fine-grained description is now needed. Gap assessment and system design are complementary efforts and must both evolve to provide a detailed depiction of the observing system to be built.

Assessing a gap between the existing system and requirements for its envisioned performance relies on definition of adequacy. Because IOOS strives to address multiple objectives with a single system, numerous specifications of adequacy for a given component will arise. Deciding on a specific measure of adequacy will involve balancing costs, weighting of requirements derived from various priorities and objectives, and implications for other system components. The time frame in which adequacy is evaluated is also important. There may be differing expectations for near-term objectives than for a design that describes the expected state of the system a decade from now. These temporal considerations are likely more of an issue for implementation planning.

Once gaps in the components of the observing system have been identified the design of a revised system that fills the gaps can begin. A number of approaches to the design process exist; indeed there is a subfield of engineering (systems engineering) dedicated to this topic. Needed is a blend of more qualitative expert knowledge, to inform the types of tools available and the ways in which they can be employed to meet requirements, and more quantitative assessment tools, such as simulation experiments, which provide an objective method for evaluating a particular design. The former can produce specific designs while the latter can be used to


optimize its structure. The design of the global system has depended heavily upon expert opinion, feasibility and available resources, with model studies useful for some components. As the breadth of priorities the system addresses increases so does the complexity of the design effort, and it should be expected that an ongoing design and evaluation program must be mounted to enable the growth of the system through infusion of new technologies in an efficient manner. The adequacy of the global ocean observing system is assessed periodically and will be revisited soon (probably by 2014) through the GCOS process. A similar practice should be adopted for IOOS.

How the design process addresses the multi-scale nature of IOOS is an outstanding question. Priorities at global, regional and local scales are likely to differ and lead to designs that may not be closely aligned, at least at certain phases of implementation. Careful consideration of the implications for interactions across scales may help identify priorities that cut across scales and provide overarching goals that define implementation timelines. A recent exploration of these issues has been undertaken by the NSF Arctic Observing Network Design and Implementation Task Force (Eicken, 2012).

U.S. IOOS is often described as a system with three functional subsystems – the Observing Subsystem, the DMAC Subsystem, and the Analysis, Modeling & Applications Subsystem – with an additional three cross-cutting areas of focus in Research & Development, Education & Training, and Governance. At a high level this abstract framework (logical/abstract architecture) encompasses the concepts in the IOOS adequately. However, as it is currently implemented (physical/implementation architecture) this system model does not quite fit. In reality IOOS more closely resembles a SoS and not a single monolithic system. This distinction is only important if we can apply it to better designing, implementing and managing IOOS.

A System of Systems (SoS) differs from a single system in a few key ways. It is typically characterized by geographic, operational, and managerial separation of the component systems (Maier, 1998). The components have been prioritized, funded and built independently (managerial separation) and do not depend on each other for their existence (operational separation). Importantly, geographic separation implies that the primary artifact that is transmitted between systems is information, emphasizing the importance of a cyberinfrastructure capable of propagating all the necessary information. For IOOS geographic connectivity, with GOOS, GEOSS and between regions within IOOS, implies the importance of ensuring interoperability between all the subsystems. Consistency of approaches to gathering and generating information will facilitate connectivity between systems. Systems of Systems evolve incrementally and iteratively because, given the managerial separation of the components, it is unreasonable to think that even the most collaborative or coordinated SoS will effect change in lock step. However, for all the difficulties in building a SoS, it is the last characteristic that provides the promise for IOOS. Systems of Systems exhibit emergent properties which is a systems engineering term expressing the well known cliche, “the whole is greater than the sum of its parts”. The IOOS should carefully consider how best to mount a comprehensive design that encompasses the full breadth of scales and topics the system is envisioned to address.

It is clear that design of US IOOS must account for the managerial separation of its existing components and the need for interoperability with larger scale (i.e. GOOS) and complementary


(e.g. Global Terrestrial Observing System (GTOS), National Ecological Observing Network (NEON)) observing systems. Challenges to moving forward include:

Short-term. Are core/essential variables the right way to bridge across the various scales global/national/regional) of U.S. IOOS focus? Which subset of the variables list provides the most benefit in connecting across the scales of observing efforts?

Longer-term. How might a SoS approach improve U.S. IOOS efforts in: Interoperability? Best practices? Standards? Community models/components?

3. The U.S. IOOS Functional Subsystems

Given the considerations of the process of gaps assessment and system design presented above we here review the subsystems of the observing system, focusing on the status of existing systems, gap assessment and design considerations.

Observing SubsystemA large number of observing programs exist, some of which are discussed below. A distinction is drawn between observations made in-situ and those made remotely, with a further breakdown based on whether an observing platform is fixed or mobile. This begins to provide the granularity necessary to support a detailed system design. The sensing that a given platform can support varies widely, based on platform characteristics and sensor load that are critical to design considerations. Ideally a design analysis should be done based on core or essential variables, but in practice it is often necessary to consider activity by platform.

In-situ observing almost always depends upon access to ships, to provide ground truth for overhead sensors, to make the observations directly, or to deploy autonomous platforms (moorings, drifters, profiling floats or gliders). Access to ships is a critical infrastructure need and requires considerable coordination among observing components, national research vessels, and commercial shipping for the global system. Talley and Feely (CWP) note that ship-based repeatable hydrography surveys is the only existing method to measure and track ocean carbon inventories, observe the global ocean below 2000 m, measure and track overall ocean heat changes, or provide the highest quality in situ validation data for autonomous sensors.

Commercial vessels have played a primary role in the historical collection of met-ocean observations and support ocean observing in other ways. In particular, some vessels deploy drifters and profiling floats and XBTs and tow plankton collection systems. Others support underway sampling systems for sea surface salinity and pCO2, and a variety of other variables potentially could be observed. The industry has indicated a willingness to support ocean observing, within agreed limits of responsibility, and it is important to follow up on recent interactions to expand the type of variables observed and the spatial coverage.

Autonomous platforms, when their arrays can be adequately maintained, offer the ability to collect observations routinely throughout much of the global ocean. Moorings offer the unique ability to sample the full time spectrum of temporal variability with high accuracy. Autonomous


platforms have revolutionized our knowledge of the ice-free global open ocean over the past decade, and much development is underway to make these systems capable of sustained operation under ice. The motivations for these autonomous systems are reduced cost of operations and continuous all-weather observing. The ability to collect observations in conditions too harsh for vessel operations (e.g. storms or under ice) and at high frequency for extended periods of time has significantly improved the statistics of ocean observations and permits greater confidence in state estimation and hence predictability.

It is essential to increase the observing capabilities of surface drifters, gliders and profiling floats beyond their present physical variables. Work is ongoing to improve the ability of biogeochemical sensors on these platforms, as well as to develop profiling floats capable of sampling the full ocean depth. There are power, stability, calibration and data system implications for every new sensor, which require sustained community engagement to address.

In coastal settings moored buoys have served as the principal automated observing platform. Moored buoys are also an essential component of the global system, both to provide information in critical regions like the tropics and to provide reference quality observations at selected global reference sites. These fixed platforms have enabled collection of long time series of largely near-surface physical variables, sufficient in some instances to define seasonal climatologies and anomalies from them. Routine collection of subsurface observations using subsurface moorings has increased in recent years but subsurface observations in coastal areas, and the use of these platforms to host a wider variety of sensors, are a significant gap (Virmani CWP). Despite the increased use of mooring, it is not practical to document the smaller spatial scales of variability characteristic of the coastal waters with these systems. Mobile platforms have proven to be an effective technology to address this need.

Regions with limited depths and strong currents pose challenges for drifters and deep-water profiling floats. Underwater gliders are a promising mobile platform for observing some parts of the coastal ocean because of the ability to capture smaller spatial scales of variability and because of the ability to direct sampling patterns and protocols. Ruddick et al. (CWP) present a plan for implementing a routine glider observing program covering coastal waters and providing a link to global observing. A number of other navigable platforms (wave gliders, autonomous underwater vehicles, autonomous ships) and volunteer observing platforms (e.g. ferry-based systems, see Codiga et al. CWP) are finding use in US coastal waters, including those areas not accessible by gliders (e.g. estuaries and the nearshore) and should be considered for inclusion in an observing subsystem design.

The collection of platforms best suited to a given region will vary due to differing environmental conditions (water depths, current strength, stratification, intensity of human activity, accessibility), payload needs, and will change over time as new capabilities become available. A comprehensive observing subsystem makes the best use of the qualities of each of the available platforms in different regions. No single platform offers a cost-effective strategy for all observing needs. The global system has long depended upon a mix of platforms to obtain global coverage at minimum cost. An important aspect of a coastal design will be accommodating


flexibility in platform use regionally and temporally to adapt to changing needs and to maximize the efficiency of operations.

Dedicated observing networks have already been considered in IOOS planning, notably the surface current mapping plan (HFR plan) and waves plan (Birkemeier, CWP). These plans consider either how best to employ a specialized observing technology (e.g. high-frequency radar) on a national scale or a specific variable of interest (directional wave field) and the best mix of platforms and sensors to enable its observation nationally. It is likely that a mix of approaches to the observing subsystem design, considering both dedicated systems and more overarching approaches that consider a broader scope (e.g., ecosystem observing network) will need to be employed.

Routine collection of biogeochemical variables is probably the greatest recognized gap in the observing subsystem. Typical methods require laboratory analyses at some stage of processing and have been ship-based. However there is in explosion in automated sensing development, as well as development of indicators or proxies of ecosystem state, that if fostered holds the promise of addressing this large gap in observing capability. The GOOS (193) explores how a balance of routine and measurement techniques at various states of readiness can be employed to acquire the needed observations.

A major challenge that IOOS faces is tackling the design of the observing subsystem. A complete and dynamic inventory is critical to ensuring efficient investment in observing, which because of the harsh ocean environment, is the most costly subsystem of IOOS. The varied ways in which observations can complicate gap filling and will benefit from objective techniques to assess impact and tradeoffs between options. Rapid technological advances are exciting but pose further challenges to design because of the unknown ways in which new technologies may impact existing components of the subsystem.

Major Observing System Ideas from Community White PapersThere is keen interest in developing new observing technologies as evidenced by the large number of community white papers submitted on this topic.

• Gledhill et al. describe observing needs to assess ocean acidification and its impacts in coastal regions and note that carbon chemistry and ecosystem response changes need to be measured together.

• Wanninkhof et al. examine the Integrated Ocean Carbon Observing System and describe a series of augmentations to existing programs that will enable improved estimates of carbon inventories and impacts.

• Acoustics-based monitoring of fisheries and marine animals, from use of existing or innovative platforms to host active acoustic survey equipment (Greene et al., Horne et al.) to continental shelf wide acoustic arrays (Welch et al., O’Dor et al) have been examined. Passive acoustics monitoring of biological and human activity may be possible from a wide variety of platforms (Southall et al.).

• Leveraging the Animal Tracking Network to enhance monitoring of a broad range of variables is also considered (Block et al), as is inclusion of line transects for observer-based biological data is promoted (Fornhall et al).


• HAB monitoring and forecasting will require integration of a range of variables, as well as observation of select toxins, at a spatial resolution that requires further investigation (Anderson et al., Kudela et al.).

• A number of community white papers explore possible industry roles and relationships to IOOS (Rossby et al., Woll et al., Holthus, Manly et al.). Given the funding challenges system build-out faces, industry collaboration may be a vital mode of capitalization.

• It will also be important to consider federal involvement and investment in GOOS regional programs. Of particular note is the Arctic, a region experiencing unprecedented change, and in dire need of a broad range of enhanced observing capabilities (Auad et al., Calder et al., Stabeno et al., Hicks et al.).

Priority should be given to international GOOS regions that impact US waters (the Arctic, Gulf of Mexico, Caribbean, Pacific) and exploring opportunities to leverage international programs to meet gap assessment and design needs.

Remote sensing data complements and enhances the value of these in situ observations (and vice versa). Platforms for remote sensing include satellites (e.g., ocean color radiometry from polar and geostationary orbits), sub-orbital (e.g., airborne Lidar) and land-based platforms (e.g, high-frequency radar: HFR). These platforms can provide synoptic, regular and (potentially) consistent physical and biological observations from regional to global scales that can be used for event-scale responses (e.g., oil spills) as well as long-term time-series analyses (e.g., sea level rise). Weaknesses, e.g., lack of sub-surface or other desired measurements and limitations in spatial, temporal and/or spectral resolution/coverage, can be addressed through complementary in situ measurements, as well as through new technology development and expanded platform/sensor deployment (see below). There are many key IOOS variables and measurements that can be derived from remotely sensed and satellite-based observations in particular. From the global climate observing perspective, ocean essential climate variables (ECVs) for which satellite observations make a significant contribution include sea-surface temperature; sea-surface salinity; sea level; sea state; sea ice; and, ocean color (GCOS, 2011). From the broader ocean and coastal observing perspective, the list is much longer and includes other ocean color, synthetic aperture radar, scatterometer and derived observations - see for example the PICO (2012) Coastal GOOS Report, especially Table 15 therein.

Numerous recent articles and reports have addressed needs for ocean remote sensing as well as current status and future directions in the field, particularly from satellite platforms, in support of GOOS (Drinkwater et al., 2010: OceanObs ‘09 Proceedings; PICO, 2012: GOOS Report #193), IOOS (Muller-Karger et al., 2012: IOOS Summit CWP), GCOS (GCOS Report #154, 2011) and for broader ocean research and applications (e.g., Lindstrom, E.J., and N. Maximenko, 2010: The Future of Oceanography from Space; Lindstrom et al., 2010 and Bonekamp et al., 2010: OceanObs ‘09 Proceedings; NRC, 2011: Ocean color requirements). Earlier reports still germane in this context include the IGOS Coastal Theme Report (2006), and the Ocean.US Report #16 (2006) – Report from Workshop on Regional Needs for Coastal Remote Sensing.


There are other relevant reports from the GEOSS context which address emerging applications such as remote sensing of water quality (e.g., GEO, 2007). Significant progress has been made the last 10 years in terms of dual-purposing space-based ocean observing capabilities for both research and operations (e.g., altimetry, scatterometry, ocean color), as well as implementing new measurements (e.g., sea-surface salinity from Aquarius; sea ice thickness from Cryosat-2) and expanding the use of satellite data to meet user needs (e.g., regional water quality monitoring using ocean color data; ocean products from Cryosat-2 to support NCEP and the National Hurricane Center). However, many needs, challenges and opportunities still exist with regard to satellite and other remotely sensed observations of the ocean as detailed in the above articles and reports. In particular, these include continuity, resolution/coverage, and knowledge challenges (IGOS, 2006; PICO, 2012), as well as integration challenges (Ocean.US, 2006) per below.

While new, successful missions have come online recently (e.g., Suomi NPP), the continuity of high quality observations in general remains a persistent concern and challenge, particularly as several missions have ceased operations recently (e.g., Envisat), with other existing missions approaching (e.g., Jason-2) or else beyond (e.g., MODIS) design life. Further, multiple data streams are critical to ensure continuity of operations. Implementing new missions in a timely manner continues to be a significant hurdle for nations and agencies to address due to cost and other considerations. From the U.S. perspective, continuity in the future will increasingly rely on data from foreign missions/sensors, particularly in those cases where the U.S. does not have the necessary space-based assets (e.g., synthetic aperture radar and scatterometry). Free, timely and sustained access to data is an ongoing challenge to address in this context, likewise robust calibration/validation and quality monitoring of measurements to ensure high quality, consistent, and useable satellite data products (e.g., Chapron et al., 2010; NRC, 2011).

Aside from this important continuity challenge, another key challenge includes acquiring space-based observations with increased spatial, temporal and spectral resolution and coverage. One key example of this is the advanced swath altimeter concept called the Surface Water and Ocean Topography (SWOT) mission being pursued by NASA and CNES, which would benefit coastal ocean as well as inland water studies. Another example is the implementation of geostationary ocean color observations. South Korea launched the Geostationary Ocean Color Imager (GOCI) in 2010 on the COMS platform; NASA is pursuing the GEOstationary Coastal and Air Pollution Events (GEO-CAPE) mission which would provide even broader benefits for U.S. coastal waters and beyond (Fishman et al., 2012). Next generation R&D satellite missions are also needed to expand our knowledge of the ocean and provide new insights, e.g., observations of ocean surface current vectors on a regular basis over the open and coastal oceans via along-track interferometry (Freeman et al., 2010).

The most widely used ground-based remote sensing technology is surface current mapping by HFR. The national plan for broad-scale coverage around the US is an example of a design employing a dedicated technology. A review of the plan to consider nested, more high-resolution systems, and additional observational capabilities, would be appropriate. There


should also be consideration of other ground-based remote sensing technologies that may provide efficient or novel methods to observe the oceans.

Expanding the extent to which ocean remote sensing observations are used for both research and operations/applications by diverse users, including their assimilation into operational models (e.g., Bayler et al. 2012 CWP), remains a challenge and more so an opportunity (e.g., PICO, 2012). Development of new and improved satellite products, addressing global, national and regional needs is required. Further, increased focus on rigorous inter-sensor comparisons, uncertainty characterization, and data merging, integration and synthesis, involving both satellite as well as in situ data, is a crucial need, likewise the development of community-consensus climate data records (Chapron et al., 2010; Drinkwater et al., 2010; GCOS, 2011; PICO, 2012).In terms of additional future challenges and needs, Drinkwater et al. (2010) identifies four key areas, some of which were already addressed above: New products; infrastructure challenges; data challenges, and new technologies for future missions. For example, revisiting a theme addressed elsewhere in this report (i.e., strengthening the non-physical components of IOOS), they identified the need for new and improved space-based ocean biology and biogeochemistry measurement capabilities. Muller-Karger et al. (2012) makes related recommendations, including stressing the need for greater integration across disciplines, and the need for strong partnerships between private, government, and education sectors to enhance remote sensing support and product development for critical coastal and deep-water regions. This CWP likewise emphasizes the need for IOOS to inform operational and research agencies of the types of observations and observing platforms required, including what types of satellite sensors need to be launched in the future to maintain continuity of observations, and the types of new observations required. An additional issue to address in the coming years is better defining the role that sub-orbital platforms (e.g., aircraft, unmanned aerial vehicles) can effectively play in regional and global data collection for IOOS.

Major Challenges for the Observation Subsystem How is the adequacy of the existing collection of observing assets best assessed and gaps

best defined? Should it be done by variable? By priority? By geographic location? Some mix of these? Who/how? What is the national process for doing this?

How should the technologies to fill gaps be identified? Should we advocate for standards or common practices across scales as a way to improve efficiency and reduce cost? Or will this stifle innovation?

How do we promote bringing new technologies into IOOS while maintaining an operational output?

Given a large gap in biogeochemical and ecosystem automated observing, should a dedicated effort be made to advance these technologies?

Data Management and Communications Subsystem Prior efforts to characterize a fully functional DMAC system have included elements from the entire data lifecycle (Hankin, 2005; Blueprint, 2010; PICO, 2012). The vision for this subsystem is for it to deliver data, collect metadata, provide analysis and visualization tools, provide for the long term preservation and reuse of all of this information, seamlessly across regional, national and global boundaries and across disciplinary boundaries. Some gaps between the existing system and the envisioned system are identified herein, and some recommendations for filling


the gaps are made. Filling the gaps requires solving organizational changes more than technical issues.

DMAC Structure The IOOS Blueprint identifies a number of functions that must be fulfilled by DMAC and describes nodes that satisfy these roles. Data assembly centers (DAC) are viewed as a central part of the DMAC architecture, yet the form these take and their roles and responsibilities within the system, especially with respect to discrete elements of the data lifecycle, are not yet certain. How should they be organized and funded? What are their responsibilities with respect to data content? Some DACs are regional, others are thematic, and still others focus on specific observing systems. At each exchange across this diverse system, there are possibilities for information incompatibility and loss.

It may be useful to compare/contrast the U.S. IOOS DMAC with Australia’s Integrated Marine Observing System (IMOS). Data Fabric is a common resource for all of IMOS. Their national Centers are integrated by a single data management framework mandated by a central governance facility. U.S. IOOS does not have that level of control of any one node so there must be a more collaborative commitment to the information needs of the whole system. But, in order to commit, the information needs must be known and documented. At this point they are not well known.

Archiving is an essential element of good data stewardship and of the IOOS data lifecycle. The standards for IOOS DMAC data dissemination are the same as those that the archive needs. The interface between a data provider and the archive should be the same as that between a data provider and the public. Archive also distributes data according to the same protocols thereby (potentially) alleviating some of the data serving burden on the data provider. Archive process relies on metadata further emphasizing the critical role data documentation plays in enabling all the functions of the system. We need to think of the scope of the information system as encompassing much more than just the environmental observations themselves but includes the entire lineage. (Rutz et al CWP) Quality Control and Quality AssuranceQuality control is recognized by the community as a key requirement but remains a challenge due to the lack of definition of processes and – perhaps most significantly - limited funding to support the implementation of mature quality control procedures. In this regard, it would be helpful to ensure close coordination between the RAs and centers of data at multiple federal agencies such as NOAA, Environmental Protection Agency (EPA), USGS, USACOE, etc., to ensure that consistent Quality Assurance/ Quality Control (QA/QC) and archiving procedures are employed across the nation. We must recognize that this issue will only increase in importance and complexity as the volume of data and data products expands dramatically in the years ahead. Ultimately, we as a community need to convey the critical importance of QA/QC – it is the process that ensures that our data and the derived products are reliable, and therefore confidently usable by the user. Usability imparts value, ensuring a return-on-investment and contributing to the sustainability of the IOOS enterprise.


An essential role of the U.S. IOOS cyber infrastructure is to provide tools to discover and access useable information about the ocean and achieving that goal is difficult. The information delivered to users must be of sufficient quality to be useful. The responsibility for assessing, documenting and improving the quality of the observations and derived products that result from IOOS activities applies to all elements of the system. Observing system operators have an obligation to keep their instrumentation and methods inline with the state of the science practices, and data users in the Analysis, Modeling & Applications Subsystem have a responsibility to view the data in light of their inherent uncertainties, and communicate back to the observing system operators when anomalies are found. The DMAC cyber infrastructure has the responsibility for delivering this information among system nodes using technologies that enable machine-to-machine interaction and unambiguous interpretation DMAC operators are unlikely to develop quality control algorithms or quality assurance protocols for instrument calibration, but they do have a role in ensuring that this information is captured and codified using relevant IT standards. Quality Assurance of Real-Time Observational Data (QARTOD) has been an effective grass-roots effort to establish best practices in QA over the last decade, and it has recently been endorsed and supported by the U.S. IOOS Program Office. It is an appropriate model for development of variable-specific QA procedures that can be adopted by all IOOS providers.

InteroperabilityMore important than the way information is requested and received over the internet (i.e. web services), is the content and structure of that information (i.e. the structure of the data in files, the conventions used to identify the data elements, and the linkages between information in a file to information resident somewhere else on the network). The ability for a system on the internet to convey information to another system is only successful if the receiving system understands the information. An often-overlooked implication is that interoperability is defined with respect to multiple systems, not as an attribute of a single subsystem, and it is therefore not only a consideration for DMAC but for the system as a whole. Argo float data files are not interoperable in and of themselves. The Argo data system as a whole may be interoperable with the modeling efforts of a university if and only if modelers at the university can 1) locate the particular Argo data of interest, and 2) request and receive the data of interest, and 3) understand the data such that it is used in the modeling efforts in a scientifically appropriate way. The cyber infrastructure must evolve according to requirements of both the Observing Subsystem and the Modeling and Analysis Subsystem.

The data storage and access component of DMAC is well-defined for data sources including in-situ buoys, HR Radar, and gridded data from satellites and models. However, there has been in large part not enough involvement from the operational modeling centers to help prioritize DMAC requirements. Too often they operate as a separate system. Clearly the operational centers assimilating data are a vital client. Other groups that must have ready access to information for the system to function smoothly include research scientists, data assimilation systems, weather forecasting offices and product developers.

Another way to promote interoperability is to broaden the interaction between instrument manufacturers and instrument operators. Metadata generation starts with the manufacturer, but placing the responsibility for digitizing instrument specifications and factory calibration results


on the instrument operator is inefficient and error prone. One possible way to address this issue is to write a standardized metadata document into contracts and purchase agreements. A self-registration goal for automated introduction of new sensors to the system is an ambition of the NSF OOI.

Interoperability is enhanced through judicious use of standards, but adopting standards does not guarantee interoperability (Blower et al., 2010; Hankin et al., 2010b). Decisions on the application of standards will involve input from the Observing, DMAC, and the Modeling and Analysis Subsystems of U.S. IOOS. More work on tools for clients is needed (this will drive compliance); Network Common Data Format (netCDF) is a standard today because the software libraries exist for so many client applications (Howlett et al CWP).

As an example, consider the flow of metadata from the Observing Subsystem through the cyber infrastructure to the Modeling and Analysis Subsystem. Metadata, or more accurately the documentation about the life cycle of data, is crucial for understanding the applicability of data to a user product or science problem. The origin of the data lifecycle begins at the sensor manufacturer. Sensor manufacturers often provide digital information about the sensor but do so in their own proprietary formats. If manufacturers were to publish this information using the same data standards that are being implemented within the cyber infrastructure, then the entire IOOS data lifecycle would be made more efficient, avoiding the need to transform or transcribe metadata, and information loss would be lessened.

Challenges ahead include: Explore the number, type, and functionality of DACs needed to support the IOOS DMAC

Subsystem. Encourage closer coordination between Regional Associations and the data centers in Federal

agencies. Make Web services distribution the primary standard for disseminating IOSS information. Adopt Quality Assurance of Real-Time Ocean Data (QARTOD) as a starting point for QA

development within U.S. IOOS Improve and formalize processes for collecting and prioritizing data requirements, and

assessing progress against the core variables.

Analysis, Modeling & Applications Subsystem

The IOOS regional ocean observing systems are intended to be comprehensive operations that include all the components necessary to collect observations and turn them into useful and meaningful information products. The Regional Associations (RAs) seek to integrate the following core components into a unified system: observing platforms and sensors; numerical models; data management and communications; product development and engagement with users; and system management. In spite of the fact that they are not included in the phrase “ocean observing systems”, numerical models are in fact an essential ingredient in the mix. Wind, wave and current nowcasts and forecasts are critical products required by a wide range of customers including the shipping industry for safe navigation, federal and state agencies for oil spill response, the U.S. Coast Guard for offshore search and rescue, coastal communities preparing for storm surges, and industry and agencies to evaluate renewable energy resources


and assist in safe and efficient operations. Model output is also used by scientists and managers to enhance ecosystem management through understanding of biological distributions and the connectivity between habitats.

The relevant time scales for model predictions range from minutes or hours for processes such as storm surge, to weeks, months or years for ecosystem or fisheries forecasts. Increasingly, there is a call for models to shed light on regional impacts due to climate change, thus calling for predictions on time scales of decades to centuries. These efforts may take the form of down-scaling forecasts of global sea level rise to the predicted effects on a specific city or regional infrastructure. Other examples would be assessments of the consequences of long-term changes in water quality parameters such as pH or dissolved oxygen, on regional ecosystem diversity, fisheries, or aquaculture.

Different RAs have different levels of involvement in numerical modeling. Some RAs confine their role to making products using the results from models run by other organizations. In addition to providing model-derived products, other RAs configure and run models for their geographic region, with some of those regional models taking advantage of U.S. Navy or NOAA global or regional atmospheric models to provide forcing. The regional ocean models are generally nested within, or derive boundary conditions from, large-scale models, which may be run by a member of the regional observing system or come from a U.S. Navy or NOAA center. Still other RAs also undertake research in order to develop model capabilities that do not yet exist, or are not of sufficient quality, for their needs. Of those RAs running numerical models, some are doing hindcasts and process studies, while others are running at least some models in a real-time forecasting, data-assimilating mode - meaning that the model runs, incorporates observations, and produces nowcasts and forecasts on a continuing basis, such that meaning can be derived from the model data as soon as it is available. This latter activity is challenging to maintain and requires considerable infrastructure to ensure computers and people are available 24 hours a day, seven days a week.

Despite the critical importance of models to the ocean observing enterprise, it is clear that there has not been balanced investment among the observing, information management, and modeling subsystems of U.S. IOOS. Unlike the DMAC and parts of the Observation Subsystems, there is no explicitly-stated vision and implementation strategy developed for the IOOS modeling subsystem. There is a wide range of modeling approaches among the various regional observing systems, and there is only ad hoc communication between the federal agencies involved in ocean modeling and regional modeling system providers. A design effort for modeling that considers the critical role of modeling in the design and evaluation of the overall observing system and in the analysis, synthesis and prediction of ocean and ecosystem state is imperative.

In addition to the need for larger-scale ocean models to provide boundary conditions on sea level, temperature, salinity, and velocity, regional models also require atmospheric forcing including all the relevant air-sea fluxes, at appropriately fine spatial resolution. Accurate freshwater input, from stream/river gauges and hydrological models, is also necessary.

The regional models should assimilate observations made within their domains. The frequency with which the models should run, and the temporal resolution of their output, depends on the


type of model and its intended use. For instance, forecasts of salmon abundance might only be needed every few weeks or months, while forecasts of coastal sea level might be needed at intervals of hours or minutes.

We are entering a new era of coastal observation where advanced coastal modeling systems can provide dramatically improved data-driven simulations, and determine optimal observing networks for stated societal goals and available resources. In the past, many simulation models used data assimilation techniques which simply force models to look like the data in the vicinity of the data. Now with more sophisticated models that take advantage of known physical, biological and chemical relationships, data can impact even remote regions that are dynamically connected. By using inverse techniques, these relationships can be further exploited to determine the impact that different observations have on defined metrics. Once we determine what quantities we want the models to simulate, we can determine the optimal sensing network for an available amount of resources. We can thus move from an era of best guesses to an era of defensible, optimized sensing networks based on established goals.

With an understanding of how model results are to be used, based on knowledge of customer needs, models should be used for Observing System Simulation Experiments (OSSEs), to help optimize observing systems by revealing which types of measurements at which locations are most important in producing a forecast of sufficient accuracy over a given area. Then, given the range of needs to be met and the budget available, the observing array can be optimized based on dynamics and known assumptions, a more rigorous and quantifiable method than just relying on experience and intuition. This should increase the accountability of observing systems, as well as expected performance. Prediction and analysis models can identify critical ocean parameters and observing locations needed to improve model skill, thus feeding vital information into the design (sensor type and placement) for future upgrades to the Observing Subsystem.

Challenges ahead include: Increase the use of modeling in assessing and designing the Observation Subsystem : How

well can issues be addressed with the present system? What metrics are appropriate for a specific issue? How can the observational subsystem be designed to have the most impact on improving these metrics?

Develop a national vision and implementation strategy for IOOS Modeling that include regional data assimilating and forecasting models and optimal observational network design

Expand the IOOS modeling test bed nationally, with broad participation by multiple RAs.

4. Summary

Formulating a design for US IOOS, as a basis for detailed cost estimation and to serve as a guideline for implementation, must take into account the many existing observing components; a Systems of Systems approach is likely to be a useful approach. Identification of core or essential variables as a way to condense a significant number of societal and scientific priorities into a manageable set of objectives has been adopted nationally and internationally; refining the list of variables to maximize interoperability across scales, and to begin definition of requirements for the observing system, is a logical next step.


While the present observing system does include a number of existing components, gaps in spatial, temporal, and topical coverage are apparent (e.g. better subsurface information in continental shelf settings, an expanded set of observed biogeochemical variables). The bulk of the community white papers addressed ways in which to fill these gaps, A process to identify and test the suitability of a given observing technology, and ways in which to assess the aggregate impact of a suite of observing techniques, is needed to deliver a system design that is efficient and economical. Design assessments using modeling tools (e.g. observing system simulation experiments) can provide an objective means to identify optimal configurations.

Careful enumeration of the attributes and configuration of all the subsystems needed for IOOS to be a vital enterprise is essential to accurate cost estimates and resource allocation. For the modeling subsystem, clarity on statistical certainty (e.g. ensembles), spatial resolution (e.g. nesting) and connections between domains (coupling) is needed. For DMAC, a process for testing architectures of various forms to assess best performance and efficiency is needed. The ways in which product development and delivery is assured should be examined to be certain that the design adequately resources this vital component of the observing system.


Overarching: Short-term. Are core/essential variables the right way to bridge across the various scales

global/national/regional) of U.S. IOOS focus? Which subset of the variables list provides the most benefit in connecting across the scales of observing efforts?

Longer-term. How might a SoS approach improve U.S. IOOS efforts in: Interoperability? Best practices? Standards? Community models/components?

Observing subsystem: How is the adequacy of the existing collection of observing assets best assessed and gaps

best defined? Should it be done by variable? By priority? By geographic location? Some mix of these? Who/how? What is the national process for doing this?

How should the technologies to fill gaps be identified? Should we advocate for standards or common practices across scales as a way to improve efficiency and reduce cost? Or will this stifle innovation?

How do we promote bringing new technologies into IOOS while maintaining an operational output?

Given a large gap in biogeochemical and ecosystem automated observing, should a dedicated effort be made to advance these technologies?

DMAC: Explore the number, type, and functionality of DACs needed to support the IOOS DMAC

Subsystem. Encourage closer coordination between Regional Associations and the data centers in Federal

agencies. Make Web services distribution the primary standard for disseminating IOSS information.


Adopt Quality Assurance of Real-Time Ocean Data (QARTOD) as a starting point for QA development within U.S. IOOS

Improve and formalize processes for collecting and prioritizing data requirements, and assessing progress against the core variables.

Analysis, modeling and applications subsystem: Increase the use of modeling in assessing and designing the Observation Subsystem : How

well can issues be addressed with the present system? What metrics are appropriate for a specific issue? How can the observational subsystem be designed to have the most impact on improving these metrics?

Develop a national vision and implementation strategy for IOOS Modeling that include regional data assimilating and forecasting models and optimal observational network design

Expand the IOOS modeling test bed nationally, with broad participation by multiple RAs.


Chapter Five: Integration Challenges and Opportunities

1. Introduction

A truly integrated ocean observing system is still an aspiration, and will remain so unless and until we as a community address integration in all of its forms. Certainly, there is strong consensus that the envisioned integrated system should provide ocean state estimates (past, present, and future) to a known degree of accuracy based on the integrated use of ocean observing networks, data management and communication tools, and data assimilative model predictions. These estimates should produce “actionable” information regarding physical, chemical, and biological characteristics delivered to the various user communities. Such information can range from scientific findings, to operational products to support safe navigation, and products in support of public education and public policy, to name a few examples. As envisioned from the outset of IOOS®, these parameter measurements and ocean state estimations should be integrated into programs that quantify the meteorological, terrestrial, and human impact/human influence drivers of change across time scales from seconds to centuries.

But this is not enough. An integrated system must engage all providers and all consumers of relevant data and data products at the local, regional, national, and global scales. It must effectively address both the physical and ecological components of the ocean state. And it must bridge the gap between basic & applied research and technology development, and between operations and technology products. We can point to several successes in the latter respect over the last 10 years. The transition of satellite products to operational use in coastal zone management (e.g., response to HABs and oil spills), and the rapid introduction of HF Radar-derived surface current maps and data assimilative high-resolution coastal models are striking examples of successful, integrated action across academia, government, and industry. But these achievements were not the result of formal and sustained partnering between the research and the operational segments of our community. There have in fact been very few opportunities for truly integrated activities where new knowledge and new technologies inform and enhance operational observing and prediction systems via well-understood transition pathways, and where conversely, requirements and lessons-learned from the observing and prediction system operators inform and guide research and development. There is a need to more effectively integrate the activities of the research and development community and the operational community across all sectors (public, private, and academic) and across all scales of interest (local, regional, national, and global). Only in this fashion can we unlock the energy, expertise and creativity of the U.S. IOOS community to successfully address the rapidly increasing societal needs for informed, safe, responsible, secure, and sustainable utilization of our ocean resources.

2. The “I” in IOOS


The need for strengthened integration among disciplines -- among observations, data product dissemination and modeling/analysis; between the research and operational communities; and among the various federal and nongovernmental organizations -- is widely accepted in today’s ocean observing and prediction community. Without the capacity to access, verify (QA/QC), and combine data and data products across multiple information types and sources, IOOS cannot function as a user-driven operational system. For this reason, ocean data integration has been a central goal of IOOS from the start, and DMAC efforts were some of the first projects supported in the early days of IOOS. A defining feature of a successful operational system is a full integration of its observing and prediction components, because it is not possible now, nor will it be in the foreseeable future, to monitor (measure) the ocean with high enough spatial and temporal resolution to provide the various user communities with the data products they require. Even if we were able to populate the ocean with an adequate number of sensors, the present-state conditions tell us very little about future conditions. Computer models enable us to fill gaps in the 4D information domain, providing estimates of ocean state variables at locations and times where we possess no direct measurement, as well as predictions of how these variables will change over time. On the other side of this integrated system, direct ocean measurements provide models with initial and boundary conditions, as well as real-time constraints, to significantly improve model performance and to enable a reasonable understanding of model skill. The remaining component of this integrated observing & prediction system is the DMAC Subsystem.

The question before us is whether the integrated observing/data management & communications modeling & analysis system -- as presently envisioned by U.S. IOOS and implemented via partnerships across the academic, public, and private sectors -- can achieve a sustainable user-driven, operational system. Some leading attributes of such operational systems are:

Composed of three Functional Subsystems: Observing, DMAC, and Modeling and Analysis

Certified to meet evolving user requirements expressed as standard metrics with known error attributes, which vary over time and space

Documented sustained sponsorship for application-dependent, real-time product delivery AND ongoing research and development with clear transition pathways

Demonstrated robust and resilient operations Design that supports both experiments and rapid response to marine crises

Success will require that we commit to the necessary periodic introspection and ensuing community-wide efforts to ensure that the U.S. Integrated Ocean Observing System moves away from a cooperative enterprise with numerous partners striving for their individual goals to a coordinated enterprise striving for a single, integrated system. Such an improved, integrated enterprise would include the following attributes:

More active participation in the 17 sponsoring U.S. federal agencies; as well as regional, state, and local agencies

Defined processes and funding to ensure robust Research-to-Operations and Operations-to-Research transitions

Defined processes to validate and prioritize requirements at the global, national, regional and local levels to inform funding and long term planning decisions


Improved integration of all requisite disciplinary fields to enable widespread and effective dissemination and use of data and data products

Improved integration of remotely-sensed data with in-situ observations and model output Improved integration of real-time data management with maintenance of long-term

archives Improved integration with ocean science and engineering workforce development, STEM

education, public policy, and public outreach.

3. Challenges to, and Opportunities for, Improved Integration

Over the past decade, success has occurred most often when efforts were made to ensure interoperability across all aspects of observing, data management & communication, and modeling & analysis subsystems. Our eventual, long-term sustained success will require that we make integration and interoperability across systems and organizations the top priority for U.S. IOOS. This must necessarily include interoperability within the U.S. IOOS network -- among the 11 RAs, the 17 sponsoring US federal agencies, private industry, and a growing number of governmental and nongovernmental organizations – as well as interoperability of U.S. IOOS assets with the international GOOS and GEOSS. This, in essence, is our challenge.

Overall IntegrationAchieving integration of all programs and activities across federal and non-federal (local and state government/private/academic) organizations will require cultural changes on all sides. The federal government cannot own sufficient platforms, sensors, models and computational and analysis systems to comprehensively and at adequate resolution cover the entire U.S. coastal ocean and Great Lakes. Academic and private industry partners must play a role as active providers of data and data products, that is to say, as “operators”. This will require trust-building, experiments, failures, and joint action to address weaknesses. It will require that the community address head-on the longstanding issues related to data and data product liability, and the use of proprietary data. Once this evolution is complete and we have moved from cooperative to coordinated in our work together, the community will be in a much stronger position to deal with the very difficult issues that challenge all science and technology programs

understanding the user needs – and therefore the requirements - for products and services the development of transition pathways for new technologies to address those

requirements This process, informed from the outset by the various user communities, will require that our operational systems be multi-disciplinary and adaptive, and that they deliver a clear return-on-investment, across the seven areas of societal benefits targeted for U.S. IOOS support.

Observations SubsystemThe ocean sciences community understands the limitations of existing observation and prediction systems to deliver all of the required information at all locations in real time. We employ models and data assimilation to fill the very large gaps in our direct observations. Although we need to do more to understand the skill of these combined systems, we have seen their impact in providing real-time and near real-time information to users, addressing important societal goals. The scientific community in all sectors – public, private, and academic – must act in a


coordinated fashion to improve and expand on these successes, which will necessarily involve increased experimentation.

Our existing observing systems are an amalgam of federal, state and local government, academic, and private systems. The integration of the data and data products from these systems into a single report of ocean conditions is impeded by a number of issues, including liability concerns (or at least the perception of liability concerns) on the part of academic institutions, and the desire to protect in some fashion the proprietary data and data products delivered by private industry. The Meteorological Assimilation Data Ingest System (MADIS), established by the National Weather Service (NWS) to collect, store, and disseminate observations from non-federal weather observing networks, has several categories that designate how contributed data will be handled, including a category for proprietary data (usually from private network operators) that is authorized for use within NOAA, but not authorized for further distribution outside of NOAA. Under the National Mesonet Program (NMP) and through the use of restricted licenses, MADIS currently receives observations from nearly 10,000 professional-grade private sector weather stations. Given the success of the NMP and the MADIS data architecture in facilitating access to large numbers of high quality weather observations via restricted licensing implementing a similar data policy and architecture for IOOS should be given serious consideration. This is a long-overdue conversation that should be pursued immediately, since failure to act will threaten continued investment by non-governmental organizations in future platforms and systems.

Another significant challenge lies in the integration of data and data products derived from physical, ecological, and biogeochemical sensors. Since its inception, IOOS has struggled with the challenge of incorporating biological observations into the IOOS architecture. The difficulty of enabling biological data interoperability within IOOS is twofold: (1) building consensus among the many different communities of practice within ocean biology and (2) the adoption by these communities of DMAC standards that will link their data collections to the IOOS integrated ocean data architecture. There has been progress. Under the Census of Marine Life, Ocean Biogeographic Information System (OBIS) a standard was implemented that would allow for integration of species observation data. This standard, Darwin Core, is a biogeographic data standard that allows for sharing of data that are spatially, temporally and taxonomically resolved. Furthermore, the standard is extensible to address other richer biological data including absence, abundance, movement, life stage, behavior and others. To that end, IOOS has recently completed, in partnership with the US Geological Survey’s OBIS-USA program, an application of Darwin Core that captures fish abundance. Similar efforts are underway for the high frequency active acoustic systems used for fish and zooplankton surveys, and for biological data from tagged animals (physical oceanographic data from tagged animals carrying CTD and similar sensors are already being imported into IOOS).

The USGS OBIS-USA team is responsible for developing biological data standards within the IOOS DMAC infrastructure, as well as contributing to the international standards for biogeographic data, Darwin Core. The result is a Marine Biogeographic (MBG) standard that that is consistent with the global Darwin Core standard while serving US and IOOS priorities. This standard enables data collectors to render their data maximally useful - the data can be located, understood (easily viewed and evaluated for suitability of use) and accessed (via web


services) by colleagues, other members of the ocean science community, decision makers, and planners. One of the great challenges of securing biological data for IOOS has been the diversity of methods used to gather biological data. The OBIS-USA and the MBG standards process offers communities of practice a means of creating benchmark documentation of their methods that also ensures that their data will mesh well with other IOOS data. While considerable challenges remain within the realm of ocean biological data collection and ocean ecosystem modeling, IOOS is addressing the uncertainties about the data themselves and the ability to synthesize the rich variety of biological information.

The U.S. IOOS community must commit to the education and training of the next generation of ocean observing professionals. Operational systems ultimately are as effective, robust, and resilient as the people who design, deploy, maintain and operate them. These are highly specialized skills gained only by doing. Some of the skills, e.g., programming and data management skills, are highly valued in other fields. Certainly, the integration of operational systems into K-12 STEM education provides opportunities to inspire young people to pursue careers associated with ocean observing.

Data Management & Communications SubsystemOcean data integration has been a central goal of IOOS from the outset, and (DMAC efforts were some of the first projects in the early days of IOOS. This focus on DMAC is understandable, since a user-driven, reliable and robust observing system cannot exist without the capacity to access, verify (QA/QC), and combine data and data products across multiple information types and sources. Users must be able to search for and retrieve the data they need, ingest these data into their analysis or visualization software and decision-support tools, and understand the source, quality, applicability and limitations of the data. Future use and reuse of these data make similar demands of data stewardship and archiving. This requires a set of recommended or required standards and protocols, employed and evaluated through a compliance and certification process, to form the framework for DMAC activity.

NOAA’s Center for Operational Oceanographic Products and Services (CO-OPS), NDBC, and the U.S. IOOS Program Office have been collaborating for several years on a data integration project that aims to increase interoperability between data providers and the user community. The joint effort has recently focused on the implementation of NDBC and CO-OPS’ Sensor Observational Service (SOS), as part of a suite of web services, offering various new protocols, formats, and an expanded set of sensor variables. This suite of new web services enhanced the data and services that CO-OPS and NDBC were already providing through traditional web pages and facilitated machine-to-machine data transfer over the internet. Both organizations have made their SOS observational data available as a collection of stations and in multiple data formats. Previously these data could only be accessed for one station at a time. Since launching this new capability, CO-OPS’ collections service has decreased the end users’ data processing time by 70% and increased their data retrieval speed by 50%. In addition, NDBC and CO-OPS SOS services are available in Comma Separated Values (CSV), Tab Separated Values (TSV), Extensible Markup Language (XML) and Keyhole Markup Language (KML) formats. KML is especially important because it is used by a variety of GIS and mapping applications to display geospatial data of interest to the oceanographic community. These integration efforts have increased data interoperability, which translates to delivering their ocean data to a wider


customer base; faster, better and with less effort. For example at CO-OPS in 2011, fully half of the 30 terabytes of data served were discovered, accessed and delivered by this suite of web services which did not exist only five years earlier. At NDBC, these services are used to automatically transmit archive data to the National Oceanographic Data Center.

The use of open standards and technologies has been at the core of the IOOS DMAC philosophy. This has allowed the academic, federal, and industry partners to retain the use of their individual tools and approaches, but also collaborate on a unified system of data sharing and access. There has been a strong focus on the development and implementation of standards to enhance interoperability, with significant progress in enabling the sharing of observations and model output between the RAs, the federal agencies, and the user community. The components of the DMAC architecture can be summarized as:

Storage and Data Formats Catalogs, Data Discovery, Metadata, and Vocabularies Quality Control Data Access Data Products

Of the components listed above, data access has been the priority within IOOS as resources and budgets have been reduced. The Data Integration Framework (DIF) pilot project carried out by the IOOS Program Office during fiscal years 2007-2010 engaged the RAs in making observations of seven core variables available via a specific web service protocol. The exercise was successful in that it provided very specific targets for the RAs. It did not define specific technologies to be used but defined specific web services (Open Geospatial Consortium SOS, Web Map Service, Web Coverage Service protocols) or Data Access Protocols (DAP). While successfully engaging the RAs, the approach also highlighted the challenges in allowing each RA to select its own path to a solution. Depending on the skill sets available in each of the organizations, new solutions were developed independently with different toolsets ranging from Java to C. Theoretically, this approach should be successful - the standards are well defined and as long as each development team delivered a tool that complied with the standard specification, they would meet the requirement. In practice however, the approach has faced numerous challenges, including the development of stovepipe solutions. There has been progress recently, including the establishment of the SOS Reference Implementation Working Group to develop a single SOS standard based on SWE (Sensor Web Enablement).

In the past year, there has been a shift in the focus from the development and recommendation of standards to the implementation of the technologies that deliver and consume compliant standards. This is a breakthrough, as a smaller subset of technical teams now focused on the solution, which frees up the DMAC teams in the RAs to focus on the implementation of these maturing technologies and the other DMAC requirements.

In a collaborative enterprise such as IOOS openness is a well-known enabler of successful system development. First, open data is essential to provide the information upon which all of the desired IOOS capabilities can be built. But, open data need not be synonymous with free data (Woll et al CWP). Beyond sharing data, sharing experience is critical to advance IOOS.


An emerging and viable business model driven by open source software development practices is resulting in profitable companies. But open source development is much more than a willingness to share code. It is a commitment to collaboration across the entire software development cycle and is enabled by tools such as online code repositories, wikis, blogs and other information sharing portals. With a commitment to open source development coupled with training in using open source tools effectively, many of the software needs of DMAC will be developed faster and with higher quality than could otherwise be accomplished (Howlett CWP). Developers within the IOOS RAs have recently begun publishing software on open source code sharing sites and as a result the level of collaboration and code reuse across the RAs has increased significantly.

The IOOS Coastal Ocean Modeling Testbed (COMT) was a unique opportunity to implement and evaluate many of the widely used technologies. A few notes on these technologies:

- Although they are open-source and intended to be community-based, they generally have one individual developer responsible for the development and maintenance of the tool. While the community may regularly provide feedback to the developer, very rarely does the community contribute to the source code. The developers are capable, but there is a limit to how much one person can manage.

- Due to the lack of funding and staffing, we do not have reliable pathways for ongoing development and transition, including rigorous testing procedures.

- The technologies have not been tested for how they may scale to manage issues such as very large data volumes.

Clearly, the challenge ahead of us is the maturation and testing of the selected technologies. The data storage and access component of DMAC is well defined for data sources including in-situ buoys, HF radar, and gridded data from satellites and models, and is evolving for glider data. The availability and use of IOOS data from the RAs in the USCG Search and Rescue Optimal Planning System (SAROPS) system demonstrates the power of defined data sharing protocols, but incorporates a brokering layer that also provides flexibility and a robust environment for mission critical applications.

There continue to be significant challenges related to the successful population of metadata and registration and subsequent discovery of metadata, data and associated web services. New catalog systems that have been developed in the traditional GIS community are being adopted for use in the ocean community, but these catalog systems are not a perfect match. They were designed to generally manage temporally static GIS-style data of feature classes and raster datasets. The ability of these catalog systems to handle time-varying point collections (e.g collections of buoys), unstructured grids and other complex time-varying datasets is still evolving. These catalog systems also require intensive work to set up and maintain and this requires a considerable commitment in terms of personnel and budgets.

In the years ahead, and in view of continued and rapid changes in information technology, DMAC should be driven with real-world use cases, emphasizing training and support for existing technology and standards, and then building incrementally as use cases dictate. The IOOS community should also take advantage of significant partnering opportunities such as exist with the NSF’s Earthscope and OOI, in part to ensure that the standards and protocols we use are


indeed the best practices available and to enable a common trust in our data assets. Social media offer tremendous opportunities for communicating in innovative ways and enabling broader community participation. It should be exploited within IOOS, providing users a place in which to share techniques and experiences. This will both raise awareness of the enterprise and hasten its development. Quality control is recognized by the community as a key requirement but remains elusive due to the lack of definition of processes and limited funding to support the implementation of mature quality control procedures.

As we move forward with innovate strategies to meet the community’s needs with respect to data management and communication, remaining flexible to new developments in information technology, we should be mindful of the expected explosive growth of data and data products in the years ahead which has the potential to overwhelm both the generators and users of the information we seek to share. The solution will require close coordination among all information providers and all users, and will likely include a reduction in the information volume, e.g., via automated (autonomous) data processing and filtering.

Modeling & Analysis SubsystemThere is an absolute necessity for numerical models to fill observational gaps in the 4D information domain, using data assimilation to provide estimates of ocean state variables at locations and times where we possess no direct measurements. Predictive algorithms provide estimates of how these variables will change over time. Models therefore provide us with the ability to deliver real-time nowcasts as well as forecasts. They can also be useful in the reconstruction of past conditions (hindcasts) and in the conduct of hypothetical scenarios (simulations), both of which can be valuable tools in areas such as emergency response and coastal ocean resource management.

The need to have model simulations and forecasts, on appropriate time and space scales, for processes including waves, ocean circulation, weather, inundation, ecosystems, and water quality, has been identified [reference?] as a core requirement that should be available in all regions ten years from now. Today, different types of models may be run independently to simulate these different properties, but some of these model types are now coupled together, and it is expected that more will be in the future.

An important consensus resulting from the IOOS Modeling and Analysis Steering Team (MAST) effort (see Ocean.US, 2008) was recognition that the academic R&D community and the federal operational forecast centers should work cooperatively on such matters as skill assessment, observing system design, prediction system experiments, etc. The committee recommended the establishment of a system of sustained but evolving regional testbeds, where ‘regional’ may include the domains of two or more of the IOOS RAs. The significant coordination and information sharing that would be required to achieve the design and operation of such testbeds and the conduct of comprehensive experiments, would move the community much further along toward the integrated public-private-academic system alluded to several times in this chapter. The assessment of model skill and the communication of model uncertainty would, in addition to improving the state of the science, help to inform the public and the various user communities of the accuracy and reliability of integrated sensor, modeling & analysis systems. Transparency and information sharing builds trust among all stakeholders, an


essential ingredient to ensure credibility and both return-on-investment and sustainability of the IOOS enterprise.

Future coordinated model development activities must support an expanded effort to couple existing ocean and atmosphere models. Several IOOS RAs have demonstrated the importance of ocean surface boundary conditions to improved atmospheric forecasts. These improved atmospheric forecasts can in turn dramatically improve the skill of coastal ocean models. In addition to the need for larger-scale ocean models to provide boundary conditions on sea level, temperature, salinity, and velocity, regional models also require atmospheric forcing including all of the relevant air-sea fluxes, at appropriately fine spatial resolution. Accurate freshwater input, from stream/river gauges and hydrological models, is also necessary.

Coordinated model development activities will also provide the opportunity for experiments with ensemble modeling of the ocean and atmosphere. We should take advantage of the existing global, national, regional, and in some RAs, local scale models. The ensembles may be constructed from a single model run with varied initial conditions or forcing, or from multiple models that have different physics and parameterizations. Ensemble forecasts also provide an estimate of uncertainty, which is vital for decision-makers. This ensemble approach would spur increased collaboration and coordination across government and non-government organizations, and would provide valuable products for use in both model enhancement and forecast skill improvement. The community witnessed first-hand the impact of ensemble modeling during the 2011 Deepwater horizon oil spill, when several models were employed in support of the response, and observations were used to inform first responders as to which models were performing best at different times and in different locations

There is a need to re-examine the sensor types and placement locations across the entire u.s. IOOS (government and non-government) enterprise, with the aim of optimizing the system’s usability, reliability, robustness, and resiliency. Prediction and analysis systems can guide this process by identifying critical ocean parameters and observing locations that would improve model skill and therefore the ocean-state estimates employed by virtually all of our user communities.


Within the next 10 years, develop a first-generation ocean-state information system that de-livers valued information at the right time to each and every consumer.

o Ensure this information system links the --global, national, regional, and local components --ecological, biogeochemical and physical components

--observing, data management and communications, and modeling and analysis subsystems

o Include ongoing and objective assessments of both the technologies and the informa-tion products provided to the various user groups, coupled to a vigorous research and development effort that addresses the next-generation system requirements.


o Initiate a multi-RA Systems Integration Pilot Project, led by the U.S. IOOS Program Office,

--Design the project along the lines of the Observing System Simulation Experiment (OSSE) described in the Community White Paper by Mooers.

--Focus on three primary goals1. Develop an activity that can serve as a high-profile challenge to one or

more integrated observing/modeling & analysis systems and involve government, private, and academic organizations

2. Develop and test a skill assessment process that includes quantitative metrics linked to both scientific issues and user community needs

3. Encourage and facilitate the exchange of information, lessons-learned, and perhaps even personnel among the various participating organizations.

Initiate a community-wide discussion, facilitated by the U.S. IOOS Program Office, of data policy (and the supporting data handling architecture) to optimize the integration of private sector data into the IOOS enterprise.

U.S. IOOS Program Office address the process and funding mechanisms for the transition of new sensors and advanced, regional modeling systems from the research world to the operational realm.


Chapter Six: The Way Forward/Recommendations

DURING/AFTER THE SUMMIT,WILL DECIDE WHETHER TO:

LEAVE ALL RECOMMENDATIONS IN INDIVIDUAL CHAPTERS

CONSOLIDATE ALL RECOMMENDATIONS INTO ONE FINAL CHAPTER

LEAVE FOCUSSED RECOMMENDATIONS IN EACH CHAPTER, BUT HIGHLIGHT HIGH-LEVEL, OVER-ARCHING RECOMMENDATIONSIN A FINAL CHAPTER


APPENDIX A: Acronyms

4D: Four Dimensional

ACT: Alliance for Coastal Technologies AMS: American Meteorological SocietyAOOS: Alaska Ocean Observing SystemARGO: Array for Real-time Geostrophic OceanographyATN: Animal Telemetry Observing Network

Blueprint: Blueprint for Full Capability BOEM: Bureau of Ocean Energy Management BON: Biodiversity Observation Network BOP: Build Out Plan

C: International Organization for Standardization approved programming languageCARA: Caribbean Regional Association CariCOOS: Caribbean Coastal Ocean Observing SystemCEOS: Committee on Earth Observation Satellites CeNCOOS: Central and Northern California Ocean Observing SystemCFA: Core Functional Areas CILER: Cooperative Institute for Limnology and Ecosystems ResearchCO-OPS: Center for Operational Oceanographic Products and ServicesCODAR: Coastal Ocean Dynamics Applications RadarCOMT: Coastal and Ocean Modeling Testbed CORE: Center for Ocean Research and EducationCSV: Comma Separated ValuesCTD: Conductivity, Temperature, DepthCWP: Community White Paper

DAC: Data Assembly Centers DAP: Data Access Protocol DART: Deep-ocean Assessment and Reporting of TsunamisDIF: Data Integration Framework DMAC: Data Management and Communications

e.g: latin for ‘for the sake of example’ECV: Essential Climate VariableEEZ: Exclusive Economic ZoneEM: Emergency Management eMOLT: Environmental Monitors on Lobster TrapsEOV: Essential Ocean Variable


http://en.wikipedia.org/wiki/International_Organization_for_Standardization

EPA: Environmental Protection AgencyESP: Environmental Sample Processor

FACA: Federal Advisory Committee ActFOC: Full Operating Capability

GBIF: Global Biodiversity Information Facility GCOS: Global Climate Observation System GDP: Gross Domestic Product GEO: Group on Earth ObservationsGEOSS: Global Environmental Observation System of SystemsGHRSST: Global High Resolution Sea Surface Temperature GIS: Geographic Information SystemGLATOS: Great Lakes Acoustic Telemetry Observation System GLERL: Great Lakes Environmental Research LaboratoryGLOS: Great Lakes Observing System GOCO: Government Owned Contractor OperatedGODAE: Global Ocean Data Assimilation Experiment GOOS: Global Ocean Observing System GOSUD: Global Ocean Surface Underway Data GTS: Global Telecommunications SystemGTOS: Global Terrestrial Observing System

HAB: Harmful Algal Blooms HFR: High Frequency RadarHYCOM: Hybrid Coordinate Ocean Model

i.e.: latin for ‘that is’ICOOSA: Integrated Coastal and Ocean Observation System Act of 2009IDIQ: Indefinite Delivery/Indefinite QualityIMOS: Integrated Marine Observing SystemIOC: Intergovernmental Oceanographic Commission IOOC: Interagency Ocean Observation CommitteeIOOS: Integrated Ocean Observing System

JCOMM: Joint Commission for Oceanography and Marine Meteorology

K-12: Kindergarten through 12th GradeKML: Keyhole Markup Language

MADIS: Meteorological Assimilation Data Ingest System MARACOOS: Mid-Atlantic Regional Association of Coastal Ocean Observing SystemMAST: Modeling and Analysis Steering Team MBG: Marine Biogeographic MTS: Marine Technology Society


NANOOS: Northwest Association of Networked Ocean Observing SystemsNASA: National Aeronautics and Space AdministrationNMP: National Mesonet ProgramNAVOCEANO: Naval Oceanographic OfficeNCEP: National Centers for Environmental PredictionNDBC: National Data Buoy CenterNEON: National Ecological Observatory NetworkNEPA: National Environmental Policy ActnetCDF: Network Common Data FormatNFRA: National Federation of Regional Associations NGO: Non-Governmental OrganizationNHS: National Hurricane CenterNOAA: National Oceanic and Atmospheric AdministrationNOPP: National Ocean Partnership Program NORLC: National Ocean Research Leadership CouncilNPOESS: National Polar-orbiting Operational Environmental Satellite System NSF: National Science FoundationNTL: Notice to LesseesNTSB: National Transportation Safety BoardNWP: National Mesonet Program NWQMC: National Water Quality Monitoring CouncilNWS: National Weather Service

OBIS: Ocean Biogeographic Information System OceanSITES: Ocean Sustained Interdisciplinary Time series Environmental observation SystemOGC: Open Geospatial ConsortiumOOI: Oceans Observatories Initiative O&M: Operations and MaintenanceORAP: Ocean Research Advisory Panel OSSE: Observing System Simulation Experiments

PacIOOS: Pacific Islands Ocean Observing System pCO2: partial pressure of Carbon DioxidepH: parts HydrogenPICO: Panel for Integrated Coastal ObservationPIRATA: Prediction and Research Moored Array in the AtlanticPORTS: Physical Oceanographic Real-Time System

QA: Quality AssuranceQARTOD: Quality Assurance of Real Time Oceanographic DataQC: Quality Control

R2O: Research to Operations R&D: Research and DevelopmentRA: Regional Associations


RAMA: The Research Moored Array for African-Asian-Australian Monsoon Analysis and PredictionRCOOS: Regional Coastal Ocean Observing Systems RDAC: Regional Data Assembly CentersROFFS™: Roffer's Ocean Fishing Forecasting Service, Inc.

S&T: Science and TechnologySAROPS: Search and Rescue Optimal Planning System SECOSS: South East Costal Ocean Observing SystemSLOSH: Sea, Lake, and Overland Surges from Hurricanes SoS: System of Systems SOS: Sensor Observational Service STEM: Science, Technology, Engineering, MathematicsSWE: Sensor Web Enablement

TOA: Tropical Ocean-Atmosphere TOPP: Tagging of Pacific Predators TRITON: Triangle Trans-Ocean Buoy NetworkTSV: Tab Separated Values

US: United StatesUSA: United States of AmericaUSACE: US Army Corps of EngineersUSCG: United States Coast Guard USGS: United States Geological SurveyUN: United NationsUNEP: United Nations Environmental Program

WCS: Web Coverage ServiceWHOI: Woods Hole Oceanographic Institution WMO: World Meteorological OrganizationWMS: Web Map Service WOCE: World Ocean Circulation Experiment

XBT: The Expendable BathythermographXML: Extensible Markup Language


APPENDIX B: DRAFT Glossary of Terms

Data

Data Integration: The process of combining data residing at different sources and providing users with unified access to the data. It involves the extraction, consolidation, and management of data from disparate systems to achieve broader capability by (functionally or technically) relating two or more data streams for the purposes of manipulation, analysis, and distribution. (Blueprint, 2010)

Data (IOOS): Data that are served in U.S. IOOS DMAC-compliant means by services that are listed in the U.S. IOOS Service Registry. (Blueprint, 2010)

Data Provider (IOOS) : An entity that operates a DAC or data archive that is certified as U.S. IOOS® DMAC compliant and that monitors the environment and supplies the data required by user groups for operational, applied, or research purposes. (Blueprint, 2010)

Data/Services Customer (IOOS): An entity that accesses data through U.S. IOOS and/or uses U.S. IOOS DMAC services. Data/services customers can be categorized into meaningful groupings according to key customer characteristics/attributes, for example, by type of user (modelers vs. end user) or type of entity (government agency, NGO, private company, academic institution, or the public at large). A customer may be either a human user or another software component. (Blueprint, 2010)

Elements

Node: An element of a system or architecture that produces, consumes, or processes information. Nodes may be organizations, classes of users, categories of people, software packages, collections of hardware, or combinations of these elements. (Blueprint, 2010)

Regional Association (IOOS) : Eleven Regional Associations (RA) serve the nation’s coastal communities including the Great Lakes, the Caribbean and the Pacific Islands and territories. RAs meet the diverse needs of users throughout the US through the design and operation of Regional Coastal Ocean Observation Systems (RCOOS). Together, the national and regional components form an integrated system. (http://www.usnfra.org/about/NFRA.html)

Models

Ocean Models: Computer ocean models are tools scientists use to numerically describe or represent ocean conditions. Models are used to forecast future states and to understand or decompose the various factors that affect or drive these conditions. The models, which


numerically represent ocean dynamics and thermodynamics, can be used to make comprehensive ocean state estimates, or ocean predictions, of currents, temperature and salinity structures, external and internal tides, surface waves, storm surges, etc. However, to make accurate ocean predictions, the models must be constrained by observations through realistic forcing and data assimilation.(http://www.ioos.gov/modeling/welcome.html)

Sponsored Models (IOOS): A model or other analytical tool that takes raw or refined ocean observation data and provides value-added output that is of such significance to the U.S. IOOS community that the output is served through U.S. IOOS. This is a distinct subset of models and analytical tools. All models and analytic tools are customers of U.S. IOOS data. Sponsored models are distinctive in that they also function as data providers. (Blueprint, 2010)

Partners and Stakeholders

Stakeholders: Government agencies (local, state, and Federal), private enterprise, public and nongovernment organizations, and science and education communities that use, benefit from, manage, or study ocean and coastal systems. (Blueprint, 2010)

Partners (IOOS): Any entity that assists U.S. IOOS with carrying out its mission and that meets one of more of the following conditions:

- Receives or contributes U.S. IOOS resources (either funding or in-kind support), excluding the legislative branch

- Is a partner or potential partner in planning, programming, or budgeting documen-tation

- Supports the development or implementation of U.S. IOOS by providing capabili-ties—products, data, expertise, or infrastructure—to U.S. IOOS. (Blueprint, 2010)

System

System: A collection of components organized to accomplish a specific function or set of functions (adapted from Institute of Electrical and Electronics Engineers Glossary of Software Engineering Terminology, p. 73). (Blueprint, 2010)

System (IOOS): A coordinated national and international network of observations and data transmission, data management and communications, and data analyses and modeling that systematically and efficiently acquires and disseminates data and information on past, present, and future states of the oceans and U.S. coastal waters to the head of tide. (Blueprint, 2010)

Subsystem (IOOS):

Functional Subsystems (IOOS): In general, U.S. IOOS functional subsystems provide the technical capability to readily access marine environment data and data products


within a fully capable U.S. IOOS. Each consists of a set of functions, hardware, software, and/or infrastructures managed by a variety of programs and entities. (Blueprint, 2010)

Observing subsystem. This subsystem comprises the collection of sensor and non-sensor marine environment measurements and their transmission from regional and national platforms. Accordingly, the observing subsystem is responsible for data quality assurance/quality control (QA/QC) and for initial metadata generation for the measurements being made and transmitted. U.S. IOOS observing subsystem data collectors transmit their data from the sensor (hardware or human) to data providers such as ocean data assembly centers (DACs) and ocean data archive centers. (Blueprint, 2010)

DMAC subsystem. This subsystem comprises the information technology (IT) infrastructure that enables the interoperable transmission of marine environment data from a data provider (U.S. IOOS observing subsystem) to a data/services customer (U.S. IOOS modeling and analysis subsystem). Similarly, this subsystem makes available DMAC-compliant data products (products derived from data such as model outputs) to end users, including U.S. IOOS customers and data product repositories. It also maintains catalogs of data and registries of observation systems that facilitate customer discovery of desired observation data. The U.S. IOOS Program Office will be responsible for coordinating the availability of the material/equipment solution, both hardware and software, for DMAC subsystem fielding and operations. This will entail leveraging existing capabilities when possible and developing, deploying, and supporting DMAC capabilities when necessary. (Blueprint, 2010)

Modeling and analysis subsystem. This subsystem comprises the U.S. IOOS-provided data, data products (products derived from IOOS data), and services used by U.S. IOOS users/customers. These users are Federal and non-Federal organizations and agencies, industry, academia, the research community, nongovernmental organizations (NGOs), tribal entities, professional organizations, and the general public. Intermediate users/customers synthesize and evaluate those data, products, and services to forecast the state of the marine environment and provide the results via reports, alerts, model outputs, or tailored analytical products to various end users/customers. This subsystem also provides the mechanism by which intermediate and end users make their requirements for IOOS data and data products known. (Blueprint, 2010)

Cross-cutting Subsystems (IOOS): In general, U.S. IOOS cross-cutting subsystems enhance the utility of U.S. IOOS functional subsystem capabilities. The U.S. IOOS cross-cutting subsystems include entities, processes, and tools that provide products and services to ensure sustainment of, and improvements to, the overall system and its usage. (Blueprint, 2010)


Governance and management subsystem. This subsystem comprises the collection of functions and activities that support U.S. IOOS in terms of policy, plans, guidance, resources, processes, tools, and infrastructure. (Blueprint, 2010)

Research and development (R&D) subsystem. This subsystem comprises the functions and activities required to gather requirements for research and development, analyze and prioritize those requirements, and facilitate cooperation among partners with R&D capabilities to satisfy identified requirements. It also includes processes to manage R&D pilot projects, conduct technology assessments, field technology enhancements, and transition technology solutions from the laboratory to the field. U.S. IOOS is not anticipated to directly run R&D laboratories or facilities, but can engage such institutions to act as agents of U.S. IOOS to perform designated R&D activities. (Blueprint, 2010)

Training and education subsystem. This subsystem comprises the entities, processes, and tools required to (1) develop and sustain a broad spectrum of educators and trainers who use U.S. IOOS information to achieve their education and training objectives and (2) create the workforce needed to develop and sustain the U.S. IOOS and produce U.S. IOOS information products, services, and tools. Educators, trainers, and students represent a significant customer base of U.S. IOOS. (Blueprint, 2010)


APPENDIX C: Authorship Table

IOOS SUMMIT DRAFT REPORT CHAPTER LEADS AND WRITING TEAM MEMBERS

Chapter One Chapter Two Chapter Three Chapter Four Chapter FiveChapter Leads Chapter Lead Chapter Leads Chapter Lead Chapter Lead

Progress the Past Decade

Zdenka Willis(Co-lead)NOAA/IOOS Program Office

David Martin(Co-lead)University of Washington

A Vision for the Future

Rick SpinradOregon State University

User Engagement and Requirements

Debra Hernandez(Co-lead)SECOORA

Cara Wilson(Co-lead)NOAA/NMFS

Observing System Capabilities: Gap

Assessment and Design

Harvey SeimUniversity of North Carolina

Integration Challenges and Opportunities

Michael BrunoStevens Institute of Technology

Writing Team Writing Team Writing Team Writing Team Writing Team Jack Dunnigan Kate Lambert

Margaret Davidson Jack Dunnigan Dave Jones David Martin

Ann Jochens Ralph Rayner Ray Toll Richard Crout Steve Weisberg

Ed Harrison Derrick Snowden Rich Signell

Rich Signell Chris Mooers Eoin Howlett Scott Glenn Leslie Rosenfeld Richard Edwing Jennifer Ewald Robert Gisiner Mitchell Roffer Bruce Bailey Ray Toll


APPENDIX D: DRAFT References and Reading List

Progress During the Past Decade

Blumberg, Dr. Alan, Present In the Moment - The Crash of US Airways Flight 1549, http://www.stevens.edu/research/faculty_news.php?news_events_id=1297, January 2009

Busalacchi, A., Celebrating a Decade of Progress and Preparing for the Future: Ocean Information for Research and Application. In Proceedings of OceanOBS’09; Sustained Ocean Observations and Information for Society (Vol.1), Venice, Itlay,doi:10.5270/OceanObs09. pp 45

Kite-Powell, Dr. Hauke Kite-Powell; Estimating Economic Benefits from NOAA PORTS® Information: A Case Study of the Columbia River, June 2010, http://tidesandcurrents.noaa.gov/pub.html

Kite-Powell, Dr. Hauke and Morrison, Dr. J. Ruairidh, Observing System Infrastructure and Economic Value, US IOOS summit white paper, July 2012

Lipa, Belina, et all; Japan Tsunami Current Flows Observed by HF Radars on Two Continents, Remote Sens. 2011, 3, 1663-1679; doi:10.3390/rs3081663, 3 August 2011

Pouliquen, S;,Hankin, S.,Keeley, R., Blower, J.,Donlon,C.,Kozyr, A.,Guralnick, R., The Development of the Data System and Growth in Data Sharing. In Proceedings of OceanOBS’09; Sustained Ocean Observations and Information for Society (Vol.1), Venice, Itlay,doi:10.5270/OceanObs09. pp 31.

Reed, J et all: Observations at our Freshwater Coast: the initial years of the Great Lakes Observing System Regional Association, US IOOS Summit White Paper, July 2012

Tamburri, Mario et all; Technologies to Meet IOOS and Societal Benefit, US IOOS SummitWhite Paper, July 2012

User Engagement and Requirements

Relevant International Documents

GOOS-125: The Integrated Strategic Design Plan for the Coastal Ocean Observations Module of GOOS (2003)

GOOS-148: An Implementation Strategy for the Coastal Module of GOOS (2005)


http://www.stevens.edu/research/faculty_news.php?news_events_id=1297

GOOS-193: Requirements for Global Implementation of the Strategic Plan for Coastal GOOS (2012)

http://www.earthobservations.org/http://www.ceos.org/

Relevant NOPP and Ocean.US Documents

Toward a U.S. Plan for an Integrated, Sustained Ocean Observing System, Report to Congress, 1999.

C-GOOS Workshop: An Integrated Ocean Observing System: A Strategy for Implementing the 1st Steps of a U.S. Plan, 1999.

Building Consensus: Toward an Integrated & Sustained Ocean Observing System, 2002 (Airlie House Report)

An Integrated Sustained Ocean Observing System (U.S. IOOS) for the U.S.: Design and Implementation, 2002

Relevant U.S. IOOS Office, IOOC Agency, and Regional Association Documents

Regional Associations' Ten Year Build Out Plan Synthesis, NFRA 2011.http://www.usnfra.org/products.html

National Operational Wave Observation Plan (March 2009).

Plan to Meet the Nation’s Needs for Surface Current Mapping (September 2009).

U.S. Integrated Ocean Observing System: A Blueprint for Full Capability Version 1.0 (November 2010).

Informational Document for General Release, U.S. IOOS HF radar data and its use by the United States Coast Guard for Search and Rescue

http://marinesciences.uconn.edu/News%20Articles/SAROPS_HFR_Informational_3Jul2012.pdf

Rapid detection of climate scale environmental variability in the Gulf of Maine, J.R. Morrison, NERACOOS, Rye, NH, N.R. Pettigrew, University of Maine, J. O’Donnell, University of Connecticut, J.A. Runge, University of Maine and Gulf of Maine Research Institute (2012)

Enhancing Stakeholder Engagement: Toward Next-Generation Product Development in the




http://www.usnfra.org/products.html

http://www.ceos.org/

http://www.earthobservations.org/

R2O Process, Carolyn Thoroughgood, MARACOOS / University of Delaware, Newark, DE, USA, Gerhard Kuska, Peter Moore, MARACOOS, Newark, DE, USA

Community White Papers

Allen, A., Berkson, J., The Integrated Ocean Observing System (IOOS) Supports Search And Rescue, US IOOS Summit Community White Paper, July 2012

Anderson, D., G. Doucette, G. Kirkpatrick, Harmful Algal Bloom (HAB) Sensors In Ocean Observing Systems, US IOOS Summit Community White Paper, July 2012

Bailey, B., M. Filippelli, M.Baker, The Need For Improved Met-Ocean Data To Facilitate: Offshore Renewable Energy Development, US IOOS Summit Community White Paper, July 2012

Birkemeier, W., L. Bernard, R. Jensen, R. Bouchard, Revising the IOOS National Wave Observation Plan, US IOOS Summit Community White Paper, July 2012

Gledhill, D., E. Jewlett, K. Arzyus, J. Newton, , J. Salsbury J. Bennet, J. Salisbury, A. Sutton, An Integrated Coastal Ocean Acidification Observing System (ICOAOS)

Glenn, S., D. Barrick, Implementation Of A National Dual-Use High Frequency Radar Network Supporting United States Coast Guard Requirements For Search And Rescue & Maritime Domain Awareness, US IOOS Summit Community White Paper, July 2012

Hall, C., M. Boatman, A. McCoy, Ocean Observations in Support of Offshore Renewable Energy Development, US IOOS Summit Community White Paper, July 2012

Lankhorst, M., F. Bahr, E. Boss, P. Caldwell, O. Kawka, M. Vardaro Data Quality Control In The U.S. IOOS, US IOOS Summit Community White Paper, July 2012

Rayner, R., IOOS Stakeholders and Beneficiaries , US IOOS Summit Community White Paper, July 2012

Send, U., U. Send, R. Weller, M. Ohman, T. Martz, F. Chavez, D. Demer, R. Feely, Opportunities And Challenges For Integrated Sustained Timeseries Observations, US IOOS Summit Community White Paper, July 2012

Simoniello, C., S. Walker, R. Myers, J. McDonnell, Creating Education and Outreach Opportunities for the U.S. IOOS

Thoroughgood, C., G. Kuska, P. Moore, Enhancing Stakeholder Engagement: Toward Next-Generation Product Development in the R2O Process, US IOOS Summit Community White Paper, July 2012


US IOOS Program Office, The U.S. IOOS Program Office Perspective on Observing System Capabilities: Gap Assessment, US IOOS Summit Community White Paper, July 2012

Observing System Capabilities – Gap Assessment and Design

IOOS Summit Community White Papers

Alexander, C., J. Thomas, K. Bennedict, W. Johnson, R. Morrison, J. Andrechik, E. Stabeneau, M. Gierach, K. Casey, R. Signell, H. Norris, R. Proctor, K. Kirby, D. Snowden, J. de LaBeaujardiere, E. Howlett, S. Uczekaj, K. Narasimhan, E. Keys, M. Trice, and J. Fredericks, Priorities For Governance Of Data Management And Communications For Ocean Observations, US IOOS Summit Community White Paper, July 2012

Bailey, B., M. Filippelli, M. Baker, The Need For Improved Met-Ocean Data To Facilitate: Offshore Renewable Energy Development, US IOOS Summit Community White Paper, July 2012

Bailey, B., F. Aikman, Y. Chao, and A. Mehra, IOOS Data Assimilation: Connecting Regional Associations and the National Backbone, US IOOS Summit Community White Paper, July 2012

Bayler, E., F. Aikman, Y. Chao, and A. Mehra, IOOS Data Assimilation: Connecting Regional Associations and the National Backbone, IOOS Summit Community White Paper, July 2012.

Birkemeier, W., L. Bernard, R. Jensen, R. Bouchard, Revising the IOOS National Wave Observation Plan, US IOOS Summit Community White Paper, July 2012

Block, B., K. Holland, D. Costa, J. Kocik, D. Fox, B. Mate, C. Grimes , A. Seitz , H. Moustahfid, M. Behzad, C. Holbrook, S. Lindley, C. Alexander, S. Simmons, J. Payne, M. Weise and R. Kochevar. Toward a US Animal Telemetry Observing Network (US ATN) for our Oceans, Coasts and Great Lakes, US IOOS Summit Community White Paper, July 2012

Colton, M., P. McEnaney, G. Leshkevich, Developing a Great Lakes Remote Sensing Community in Support of IOOS/GLOS, US IOOS Summit Community White Paper, July 2012

Crowley, M., H. Seim, A. Jochens, J. Quintrell, D. Hernandez, J. Kohut, R. Morrison, M. McCammon, H. Price, L. Rosenfeld, S. Skelley, J. Thomas. Building Coastal IOOS for the Next Decade: Following up on the Regional Build Out Plans, US IOOS Summit Community White Paper, July 2012

Dekker, T., J. DePinto, S. Ruberg, M. Colton, J. Read, D. Schwab, N. Booth. Design Of The Great


Lakes Observing System Enterprise Architecture, US IOOS Summit Community White Paper, July 2012

DiGiacomo, P., T. Malone, Requirements for Global Implementation of the Strategic Plan for Coastal GOOS, US IOOS Summit Community White Paper, July 2012

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APPENDIX E: Synopsis Table for Chapter One










APPENDIX F: Draft Chapter Three Summary Table

# User Engagement Step

Challenge Recommendation

1 Identify the users How can we identify the users of U.S. IOOS?

1: Organize information about users, their requirements and available products into a “marketplace”

2 Prioritize users or products

2A: How can different federal agencies, different countries and different RAs agree on priorities since resources are not available to meet all user requirements?

2A(i): Develop an “Action Agenda” for U.S. IOOS that prioritizes near-term investments and steps along the path to a fully operational system.

2A(ii): Devote a portion of each IOOC meeting agenda to resolving coordination issues

2B: There are cultural challenges involved with different communities working together, and each have a different attitude or perception on user requirements.

BC: The IOOC agencies should provide recognition, incentives and/or rewardsfor partnerships across cultural interfaces.

3 Define Requirements

3A: How can the requirements of users be better documented and communicated to U.S. IOOS stakeholders?

3A: Institutionalize a process to identify, vet and prioritize user requirements. If setup correctly this will make clear to users what is available, as well as makes clear to data providers where the gaps and opportunities are.

3B: There is a mismatch between many of the user needs and the technical capabilities of the observing system.

3B: U.S. IOOS needs to invest in the development of the necessary biological and chemical sensors to meet established user requirements.

4 Develop Solutions

4: How can we ensure that users are properly engaged in the transition from research to operations for observational data streams and models?

4A: Organize existing U.S. IOOS user engagement efforts into an ad hoc UserEngagement Council

4B… Open up the federal agency ‘pull’ opportunities …4C: Incentives for private industry ???

5 Effective Outreach

5: How can the public and other potential users be made more aware of the data available

5: Increase support to the NFRA Education and Outreach Council.
