“Multi-functional Mesoscale Observing Networks in Support of Integrated Forecasting Systems” A Report on a USWRP Workshop Organized by: Fred Carr, University of Oklahoma Walt Dabberdt, Vaisala Inc. Tom Schlatter, NOAA/OAR/FSL & CIRES Presentation to : WSN05 Toulouse, France
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“ Multi-functional Mesoscale Observing Networks in Support of Integrated Forecasting Systems”
“ Multi-functional Mesoscale Observing Networks in Support of Integrated Forecasting Systems”. Presentation to : WSN05 Toulouse, France. A Report on a USWRP Workshop Organized by: Fred Carr, University of Oklahoma Walt Dabberdt, Vaisala Inc. Tom Schlatter, NOAA/OAR/FSL & CIRES. - PowerPoint PPT Presentation
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“Multi-functional Mesoscale Observing Networks in Support of Integrated Forecasting Systems”
A Report on a USWRP WorkshopOrganized by:
Fred Carr, University of Oklahoma Walt Dabberdt, Vaisala Inc.Tom Schlatter, NOAA/OAR/FSL & CIRES
Modeling & Data Assimilation Recommendations:Scope
What is the optimal mix of observations at the meso-, storm- and urban scales?
Examples of mesoscale forecast applications requiring improved observing capabilities include:
severe weather systems in both cold and warm seasons; air quality and chemical emergency response; aviation, marine and surface transportation; and hydrology and more.
Modelers should be involved in the observing network decision process by designing observing system experiments to determine:
the most important variables to measure; the minimum spacing and resolution requirements (network design); adaptive and targeted sampling strategies; and data assimilation techniques to effectively use these new measurements.
Modeling & Data Assimilation Recommendations: Remedy Deficiencies in Current Observational Networks
Most desirable additional measurements: Lower tropospheric measurements:
– Mass, winds, moisture fields (3D) ~10 km horizontal; ~200 m vertical; 1-3 hrs– PBL turbulent fluxes, PBL heights– Turbulent flow and stability ~2 km; 15 min– Aerosols, chemical tracers, emissions data
Quantitative precipitation estimate:– Better accuracy, good and consistent quality control
Upper tropospheric measurements:– State variable measurements at 100 km spacing (0.5 km vertical), 1-3 hours– improved winds from satellite and regional aircraft – vertical profiling of state variables and hydrometeors in cloudy regions– increased vertical resolution from satellite– ozone profiling; – tropopause topology
Land surface properties: – Soil moisture and temperature profiles, snow cover and depth, SST, vegetation type/state updated daily
Radiative transfer inputs: – Ozone, CO2, water vapor, clouds
Modeling & Data Assimilation: Overarching Recommendations
It may be more cost effective to sample only the boundary layer with denser coverage than to similarly enhance observations in the upper troposphere for improving mesoscale analysis and prediction.
It may be cost effective to deploy intermittent, targeted observations at high resolution. Testbeds built around prototype observing networks need to be in place to provide real-data tests of proposed strategies
Testbed Definition: “A working relationship in quasi-operational framework among forecasters, researchers, private-sector, and government agencies aimed at solving operational and practical regional problems with a strong connection to end-users.”
Mesoscale weather research Forecast and dispersion models: development and verification Observing systems and strategies: test and design Information systems and technology integration End-user product development and demonstration Data distribution for public and research community
Implementation of Integrated Mesoscale Observing-Forecasting Systems
Focus: Explore the potential for forming a consortium of public-private-academic partners to implement a national mesoscale observing network based on the needs of the user communities, including:
A partnership arrangement was proposed for creation of consortia to develop, maintain and support regional mesoscale networks or even a composite national network.
The proposed network(s) would consist of a mix of privately owned measurement systems, publicly owned systems and newly acquired systems supplied by the consortia.
Each consortium collects and quality-controls the data, and supports the real-time dissemination of data and information products (e.g. analyses and forecasts).
Consortium members share rights, costs and revenues according to a “participation formula” (tbd)
Typical member roles: The public sector members access the data for the public good; i.e. public safety. The private-sector consortium members (and possibly academic partners) use the
data to create and sell various value-added products. Academia and non-profit research centers have access to the data for educational
Adopt the testbed concept as a priority mechanism for transitioning mesoscale observing and modeling advances from research to operations
Form a multi-sector “tiger team” to develop a functional design for a working testbed, and recommend one or more testbeds for the most pressing unmet requirements.
Develop alliances among public agencies who have complementary mesoscale needs (e.g. NOAA/NWS; Dept. of Homeland Security; EPA; DoD) to leverage resources and minimize costs.
Develop partnerships among the public, academic and private sectors that will facilitate the establishment and ongoing support of mesoscale testbeds and, subsequently, operational mesoscale observing-forecasting enterprises