NPOESS NPOESS Entering a New Era Entering a New Era National Polar-orbiting Operational National Polar-orbiting Operational Environmental Satellite System Environmental Satellite System Delivering Global Data for Improved Numerical Delivering Global Data for Improved Numerical Weather Prediction Weather Prediction AMS Symposium on the 50 AMS Symposium on the 50 th th Anniversary of Anniversary of Operational Numerical Weather Operational Numerical Weather Prediction Prediction John D. Cunningham John D. Cunningham System Program Director System Program Director College Park, Maryland College Park, Maryland
29
Embed
Tri-agency Effort to Leverage and Combine Environmental Satellite Activities
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
NPOESSNPOESSEntering a New EraEntering a New Era
National Polar-orbiting Operational Environmental National Polar-orbiting Operational Environmental Satellite SystemSatellite System
Delivering Global Data for Improved Numerical Delivering Global Data for Improved Numerical Weather PredictionWeather Prediction
AMS Symposium on the 50AMS Symposium on the 50thth Anniversary Anniversary ofof
John D. CunninghamJohn D. CunninghamSystem Program DirectorSystem Program Director
College Park, MarylandCollege Park, Maryland14-17 June 200414-17 June 2004
2NPOESS Program Overview John D. Cunningham
MissionMission
• Provide a national, operational, polar-orbiting Provide a national, operational, polar-orbiting remote-sensing capabilityremote-sensing capability
• Achieve National Performance Review (NPR) Achieve National Performance Review (NPR) savings by converging DoD and NOAA savings by converging DoD and NOAA satellite programssatellite programs
• Incorporate new technologies from NASAIncorporate new technologies from NASA
• Encourage International CooperationEncourage International Cooperation
Saves as much as $1.3B from the cost of previously planned Saves as much as $1.3B from the cost of previously planned separate developmentsseparate developments
METOP
NPOESS
Specialized Satellites Local Equatorial
Crossing Time
1730
1330
2130
NPOESS
NPOESS
Tri-agency Effort to Leverage and Combine Environmental Satellite Activities
3NPOESS Program Overview John D. Cunningham
The “Challenge” of Meteorological Satellite Convergence
Eight major “Convergence Studies” (1972-1991) • Examined consolidation of
– DoD’s Defense Meteorological Satellite Program (DMSP)– DOC’s Polar-orbiting Operational Environmental Satellite (POES) Program
• Primarily motivated by budget reduction/cost savings pressures
Studies resulted in retaining two separate programs• Deemed “highly complementary”; however• Remained separate primarily due to over-riding policy issues • Similar spacecraft with many common components and subsystems• Some measure of modest coordination/cost-savings achieved• Policy and programmatic benefits of two separate systems outweighed projected
cost savings and advantages
Achievement of Achievement of significantsignificant cost savings while still satisfying cost savings while still satisfyingcivil and military mission requirements now a civil and military mission requirements now a drivingdriving priority priority
Achievement of Achievement of significantsignificant cost savings while still satisfying cost savings while still satisfyingcivil and military mission requirements now a civil and military mission requirements now a drivingdriving priority priority
4NPOESS Program Overview John D. Cunningham
DMSP (Defense Meteorological
Satellite Program)
EOS (Earth Observing
System)
NPOESS (National Polar-orbiting
Operational Environmental Satellite System)
Sensor data rate: 1.5 MbpsData latency: 100-150 min.
1.7 GigaBytes per day (DMSP)6.3 GigaBytes per day (POES)
NPOESS Satisfies Evolutionary Program Needs with Enhanced CapabilitiesNPOESS Satisfies Evolutionary Program Needs with Enhanced CapabilitiesNPOESS Satisfies Evolutionary Program Needs with Enhanced CapabilitiesNPOESS Satisfies Evolutionary Program Needs with Enhanced Capabilities
5NPOESS Program Overview John D. Cunningham
Building A More Capable SystemThe Historical Context
First Image from TIROS-1 EOS-Aqua MODIS Image-250 m
Saharan Dust off the Canary Islands18 February 2004
Converged Requirements Provide Foundation for Combined ProgramConverged Requirements Provide Foundation for Combined Program Converged Requirements Provide Foundation for Combined ProgramConverged Requirements Provide Foundation for Combined Program
7NPOESS Program Overview John D. Cunningham
Atmospheric Vertical Temperature ProfileHighly accurate measurement of the vertical distribution of temperature in the atmosphere in layers from the surface to 0.01 mb
Major Applications
1) Initialization of Numerical Weather Prediction Models
2) Complementary data for derivation of moisture/pressure profiles and cloud properties
Integrated Operational Requirements Document (IORD) Example
Iterative, Disciplined Iterative, Disciplined Requirements Process Requirements Process
Ensures Users Needs are MetEnsures Users Needs are Met
Iterative, Disciplined Iterative, Disciplined Requirements Process Requirements Process
Ensures Users Needs are MetEnsures Users Needs are Met
8NPOESS Program Overview John D. Cunningham
NPOESS EDR-to-Sensor Mapping
Precipitation Type/Rate
Sea SFC Height/TOPO
Solar IrradianceSupra-Therm-Aurora PropSurface Type
Suspended MatterTotal Water ContentVegetative Index
Surface Wind Stress
Snow Cover/Depth
Cloud Top PressureCloud Top TemperatureDown LW Radiance (Sfc)Down SW Radiance (Sfc)Electric Fields
Energetic IonsGeomagnetic Field
In-situ Plasma FluctuationIn-situ Plasma Temp
Med Energy Chgd Parts
Net Solar Radiation (TOA)Neutral Density ProfileOcean Color/ChlorophyllOcean Wave CharacterOutgoing LW Rad (TOA)O3 – Total Column Profile
Electron Density Profile
Ionospheric Scintillation
Ice Surface Temperature
Land Surface TempNet Heat Flux
Imagery
Sea Surface Winds
Aerosol Refractive IndexAlbedo (Surface)Auroral BoundaryAuroral Energy DepositionAuroral Imagery
Cloud Cover/LayersCloud Effective Part SizeCloud Ice Water PathCloud Liquid WaterCloud Optical ThicknessCloud Particle Size/DistribCloud Top Height
Reliable and timely collection, Reliable and timely collection, delivery, and processing of delivery, and processing of quality environmental dataquality environmental data
Reliable and timely collection, Reliable and timely collection, delivery, and processing of delivery, and processing of quality environmental dataquality environmental data
11NPOESS Program Overview John D. Cunningham
NPOESS Operational Concept
1. Sense Phenomena
2. Downlink Raw Data
3. Transport Data to Centrals for Processing
Monitor and Control Satellites and Ground Elements
4. Process Raw data into EDRs and Deliver to Centrals
Full Capability at each Central
T
O
B
S
L
A
T
M
L
C
L
FOG
L
R
N
TATM
TSKY
ei
j
Field Terminals SafetyNet
Receptors
Global fiber network connects 15 receptors to Centrals
NPP Data & Control Flow NPOESS Data & Control Flow CLASS ADSNOAA Comprehensive Large Array Data Stewardship System NPP Archive & Distribution Seg
SvalbardSvalbard
13NPOESS Program Overview John D. Cunningham
NPOESS Satellite
CMIS
VIIRS
CrIS
ATMS
ERBSOMPS
NPOESS 1330 Configuration
Single Satellite Design with Common Sensor LocationsSingle Satellite Design with Common Sensor Locations Single Satellite Design with Common Sensor LocationsSingle Satellite Design with Common Sensor Locations
1330 1730 2130
VIIRS X X X
CMIS X X X
CrIS X X
ATMS X X
SESS X
OMPS X
ADCS X X
SARSAT X X X
ERBS X
SS X X X
ALT X
TSIS X
APS X
14NPOESS Program Overview John D. Cunningham
SafetyNet – The Key to Low Data Latency and High Data Availability
SafetyNet -- 15 globally distributed SMD receptors linked to the centrals via SafetyNet -- 15 globally distributed SMD receptors linked to the centrals via commercial fiber -- enables low data latency and high data availabilitycommercial fiber -- enables low data latency and high data availability
SafetyNet -- 15 globally distributed SMD receptors linked to the centrals via SafetyNet -- 15 globally distributed SMD receptors linked to the centrals via commercial fiber -- enables low data latency and high data availabilitycommercial fiber -- enables low data latency and high data availability
75% of NPOESS Data Products at the Nation’s Weather Centrals within 15 min........the rest in under 30 min
15NPOESS Program Overview John D. Cunningham
Average Data Latency
Latency (minutes)
16NPOESS Program Overview John D. Cunningham
Mission Data Flow
Timely, Accurate, Reliable Data from Sensors to UsersTimely, Accurate, Reliable Data from Sensors to UsersTimely, Accurate, Reliable Data from Sensors to UsersTimely, Accurate, Reliable Data from Sensors to Users
Space Vehicle 2
C3SDHN &
FEP(@ IDPS)
IDP@
Centrals
C3S
Sensors Bus
Space Vehicle 1
IDPS
Centrals SMD
Field Terminals (LRD, HRD)
FieldTerminalSoftware
SARSAT, ADCSTerminals
CONUS Gateways
(4x)
SMD
LRD
HRD
Space Vehicle 3Ground
Receptor
GroundStation
Mission Management Center
Space Vehicle 2
Stored Mission Data flow forCentrals and Science Data Users
C3SDHN &
FEP(@ IDPS)
IDP@
Centrals
IDP@
Centrals
C3S
Bus
Space Vehicle 1
IDPS
Science Users
SMD
Field Terminals (LRD, HRD)
FieldTerminalSoftware
FieldTerminalSoftware
HRD, LRD Data flow for Field Users
Field Users
CONUS Gateways
(4x)
Space Vehicle 3Ground
Receptor
GroundStation
Mission Management Center
Deliver DataProducts
Long TermArchive
Deliver DataProducts
Sensors
17NPOESS Program Overview John D. Cunningham
Interface Data Processing Segment (IDPS) Functional Diagram
Data Delivery Subsystem
DataFormatting
Production Schedulingand Control
Infrastructure Subsystem
Data ManagementSubsystem
On-LineData Storage
Processing Subsystem
SDR/TDRGeneration
EDRGeneration
Ingest Subsystem
Sensor DataAncillary DataAuxiliary Data
Cal/ValSubsystem
Data Quality Monitoring
CentralSystems
Long Term
Archive
Science Data
Segment
Command,Control, and
CommunicationsSegment
StoredMission
Data
RawData
RecordsData
Records
Sensor/TempData
Records
RawData
Records
EnvironmentalData
Records
FormattedData
Products
IDPOperator
CVSOperator
FormattedData Products
18NPOESS Program Overview John D. Cunningham
High performance IBM computing hardware• Each Central has a complete system (IDP) that will generate all products within
required latencies• Each IDPS or Central contains an Operations string, an Integration and Test (I&T)
string, and shared disk arrays (RAID)• Operations string carries 100% reserve capacity and additional availability
processors• I&T string can be used for integration and test of new software, support for
technology insertion, parallel operations, failover, and algorithm developmentModular, workflow-managed software
• Receives multiple data streams from C3S, processes data into RDRs, SDRs, TDRs, and EDRs, packages products into form useful for Centrals, and delivers requested products to end users
• Centrals have control over what products are created, which ancillary data sets are used, and how products are delivered
Same software is used in field terminals• Will be made available worldwide via download from the internet
Interface Data Processing Segment Approach
19NPOESS Program Overview John D. Cunningham
Current End-to-End EDR Latency
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 5 10 15 20 25 30 35 40 45 50
Time from Observation to Delivery (minutes)
Per
cen
t o
f E
DR
Pro
du
cts
Del
iver
ed
28
77%
NPOESS EDR Processing Timeline
Requirement: 95% of data delivered within 28 min. Capability: Delivering in 24.1 minutes
Requirement: 95% of data delivered within 28 min. Capability: Delivering in 24.1 minutes
Requirement: >77% of data delivered within 15 min. Capability: Delivering 80.3%
Requirement: >77% of data delivered within 15 min. Capability: Delivering 80.3%
Average < 10 minAverage < 10 min
Earliest Data Delivered < 3 minEarliest Data Delivered < 3 min
20NPOESS Program Overview John D. Cunningham
Comprehensive Risk Reduction
Validate technological approach to remote sensing
Early delivery of NPOESS data to users
Sensor demonstrations on non-operational platforms• Lower risk to operational users• Lower risk of launch delays due to operational schedule
• NPP Spacecraft contract awarded to Ball Aerospace – May 2002• Instrument Risk Reduction – 2006 Launch• Early delivery / instrument-level test / system-level integration and test
• VIIRS - Vis/IR Imager Radiometer Suite (IPO)VIIRS - Vis/IR Imager Radiometer Suite (IPO)• CrIS - Cross-track IR Sounder (IPO)CrIS - Cross-track IR Sounder (IPO)• ATMS - Advanced Technology Microwave Sounder (NASA)ATMS - Advanced Technology Microwave Sounder (NASA)• OMPS – Ozone Mapping and Profile Suite (IPO)OMPS – Ozone Mapping and Profile Suite (IPO)
• Provides lessons learned and allows time for any required modifications before NPOESS first launch
• Ground System Risk Reduction• Early delivery and test of a subset of NPOESS-like
ground system elements
• Early User Evaluation of NPOESS data products
• Provides algorithms / instrument verification and opportunities for instrument calibration / validation prior to first NPOESS launch
• Allows for algorithm modification prior to first NPOESS launch
• Continuity of data for NASA’s EOS Terra/Aqua/Aura missions
22NPOESS Program Overview John D. Cunningham
Real-Time Operational Demonstrations
NPP (2006)CrIS/ATMS
VIIRSOMPS
Aqua (2002)AIRS/AMSU/HSB & MODIS
METOP (2005)IASI/AMSU/MHS & AVHRR
NPOESS (2009)CrIS/ATMS, VIIRS, CMIS,
OMPS & ERBS
CoriolisWindSat
(2003)
NWS/NCEP
GSFC/DAO
ECMWF
UKMO
FNMOC
Meteo-France
BMRC-Australia
Met Serv Canada
NWS/NCEP
GSFC/DAO
ECMWF
UKMO
FNMOC
Meteo-France
BMRC-Australia
Met Serv Canada
NWPForecasts
NWPForecasts
NOAA Real-Time Data Delivery TimelineGround Station Scenario
NOAAReal-time
UserC3SC3S IDPSIDPS
Joint Center for Satellite Data Assimilation
Use of Advanced Sounder Data for ImprovedUse of Advanced Sounder Data for ImprovedWeather Forecasting/Numerical Weather PredictionWeather Forecasting/Numerical Weather Prediction
23NPOESS Program Overview John D. Cunningham
Current Satellite Data Support forNumerical Weather Prediction
Over 97% of the data ingested into the data assimilation system is derived from satellite data (LEO, GEO, operational, and experimental)...Dr. Louis Uccellini, Director, NCEP, 2003• POES provides 86% of satellite data for NCEP prediction
models [Worldwide forecast models mostly use satellite sounding data which is primary mission of POES and secondary on DSMP] …Dr. Stephen Lord, Director, EMC/NCEP –ATOVS temperature super-obs produced the largest reduction in
72h forecast error of any observation type • Early study results indicate advanced sounders with
capabilities similar to those being developed for NPOESS (e.g., CrIS and ATMS) indicate measurable positive impact on model accuracy - European Centre for Medium Range Weather Forecasts
24NPOESS Program Overview John D. Cunningham
• Before the availability of satellite sounding data, useful forecasts for the Southern Hemisphere were limited to data rich areas such as New Zealand and Australia and these were limited to very short range (i.e., < 2 days).
• Today Southern Hemisphere forecasts have about the same scale and useful range as Northern Hemisphere forecasts, primarily the result of the global satellite sounding system.
G.A.Kelly (ECMWF)
Satellite Soundings and Forecast SkillCourtesy Dr. Bill Smith
25NPOESS Program Overview John D. Cunningham
Higher Spectral Resolution Soundings
Data from atmospheric sounders provide the primary input to Numerical Weather Prediction models at Operational Processing Centers
Current fidelity NPOESS
fidelity
More Channels
Better Soundings
Radiances andTemperature & Moisture Profiles
NPOESS will deliver higher spectral resolution soundings NPOESS will deliver higher spectral resolution soundings with improved data latency to initialize NWP models and with improved data latency to initialize NWP models and
NPOESS will deliver higher spectral resolution soundings NPOESS will deliver higher spectral resolution soundings with improved data latency to initialize NWP models and with improved data latency to initialize NWP models and
•Orders of magnitude increase in data volume from NPOESS will require commensurate increases in computational power for data assimilation and modeling•How can we make best use of higher spatial and temporal
resolution data through assimilation •New methods will be required to take advantage of higher spectral
resolution data from atmospheric sounders (CrIS, AIRS, and IASI)•How can all the radiance information be used in NWP – as
radiances or retrievals?•How do we take advantage of improved data latency?
•More rapid update cycles through 4-dimensional data assimilation•What is the impact of clouds on soundings?
•How do we use VIIRS for enhancing high vertical resolution CrIS retrieval reliability above clouds
•How can we use ATMS/CMIS for providing sub-cloud level profile information?
NPOESS Challenges for NWP
27NPOESS Program Overview John D. Cunningham
Five Order of Magnitude Increase in Satellite Data Over Next Ten YearsFive Order of Magnitude Increase in Satellite Data Over Next Ten YearsFive Order of Magnitude Increase in Satellite Data Over Next Ten YearsFive Order of Magnitude Increase in Satellite Data Over Next Ten Years
Count
(Mill
ions)
Daily Satellite Observation Count
20001990 2010 2010-10%of obs
2002 100 M obs
NPOESS Era Data VolumeCourtesy Dr. Stephen Lord
2003 125 M obs
28NPOESS Program Overview John D. Cunningham
Expected NPOESS Instrument Impact on NWS Forecast PerformanceCourtesy Dr. Stephen Lord