Polar Orbiting Satellite Data in NWP Present and
Polar Orbiting Satellite Data in NWP – Present and Future Dr. Louis W. Uccellini Director, National Centers for Environmental Prediction Polar Max Silver Spring, MD October 26, 2005 “Where America’s Climate, Weather and Ocean Services Begin”
Overview • The NOAA Prediction Process • Joint Center for Satellite Data Assimilation 2
The NOAA Prediction Process 3
The Path to NOAA’s Seamless Suite of Products and Forecast Services To Serve Diverse Customer Base Observe e. g. , National Association of State Energy Officials, Emergency Managers, Water Resource Agencies, … Products & Forecast Services Process Central Guidance Local Offices Respond & Feedback IBM Supercomputer at Gaithersburg, MD Computer Center Distribute Research, Development and Technology Infusion Feedback 4
Need for a Balanced Approach • Global observations – – Oceans Atmosphere Land Cryosphere • Numerical Prediction Models • Computational Power/Communications • Forecasters 5
Global Observations 12 UTC 6 hour window Global Rawinsondes Aircraft Wind/Temp Reports Polar Satellite Radiances (2 sat) Marine Obs -- 12 Hour Total DMSP Imager – Sfc winds/PW Satellite Winds 99. 99% of data derived from satellites 6
Model Dependencies: Basis for How Predictions are Made Medium Range Ensemble (NAEFS) G L O B A L GFDL Hurricane Dispersion Global Forecast System D A T A North American Mesoscale Model (NAM) Ocean Climate Forecast System Ocean Air Quality Forecas t Short-Range Ensemble NOAH Land Surface Model Severe Weather Aviation Hourly Forecast
The Environmental Forecast Process Observations Has implications for how to apply CAL/VAL to future instruments Data Assimilation Analysis Model Forecast Post-processed Model Data Numerical Forecast System Forecaster User (public, industry…) 8
Computing Capability $26. 4 M/Year Investment Commissioned/Operational IBM Supercomputer in Gaithersburg, MD (June 6, 2003) • Receives Over 210 Million Global Observations Daily • Sustained Computational Speed: 1. 485 Trillion Calculations/Sec • Generates More Than 5. 7 Million Model Fields Each Day • Global Models (Weather, Ocean, Climate) • Regional Models (Aviation, Severe Weather, Fire Weather) • Hazards Models (Hurricane, Volcanic Ash, Dispersion) • 3. 2 x upgrade operational on January 25, 2005 • Backup in Fairmont, WV operational January 25, 2005 9
Production Generation Summary: Sustaining “On Time” Delivery Popularity of NCEP Models Web Page 2001 2002 2003 2004 2005 10
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Reasons behind improvements • Began using satellite radiances in 94 -95 • Began using “raw” radiances (as opposed to cloudcleared) 98 -99 • Other improvement due to a balance among – Observations – Data Assimilation & Model technology – Computing resources • Estimated 30 -40% of improvement from observations (principally global LEO satellite data) and 60 -70% from data assimilation and modeling techniques and computing resources 12
The Joint Center for Satellite Data Assimilation • Formed in 2001 • Infrastructure for real-time access to operational and research satellite data from GOES, AMSU, Quikscat, AIRS, MODIS, … • Community fast forward radiative transfer scheme … operational data assimilation and model forecast systems available to research and forecast communities • Supports “internal” and “external research” and data assessments on NOAA/NCEP computers The Research Community is now using the operational infrastructure. The Operational Community is now accelerating use of satellite 13 data.
JCSDA Mission and Vision • Mission: Accelerate and improve the quantitative use of research and operational satellite data in weather and climate analysis and prediction models • Near-term Vision: A weather and climate analysis and prediction community empowered to effectively assimilate increasing amounts of advanced satellite observations • Long-term Vision: An environmental analysis and prediction community empowered to effectively use the integrated observations of the GEOSS – and be ready for NPOESS at “Day 1” after launch 14
NPOESS Era Data Volume Daily Satellite & Radar Observation Count 2005 210 M obs 2003 -4 125 M obs Count (Millions) Level 2 radar data 2 B 2002 100 M obs 1990 2000 2010 -10%of obs Five Order of Magnitude Increase in Satellite Data Over Next Ten Years 15
Satellite data used operationally within the NCEP Global Forecast System (2005) HIRS sounder radiances AMSU-A sounder radiances AMSU-B sounder radiances GOES 9, 10, 12, Meteosat atmospheric motion vectors GOES precipitation rate SSM/I ocean surface wind speeds SSM/I precipitation rates TRMM precipitation rates ERS-2 ocean surface wind vectors Quikscat ocean surface wind vectors AVHRR SST AVHRR vegetation fraction AVHRR surface type Multi-satellite snow cover Multi-satellite sea ice SBUV/2 ozone profile and total ozone AIRS 16
JCSDA Road Map (2002 - 2010) 3 D VAR ---------------------------4 D VAR By 2010, a numerical weather prediction community will be empowered to effectively assimilate increasing amounts of advanced satellite observations Resources: NPOESS sensors ( CMIS, ATMS…) GIFTS, GOES-R Science Advance OK Required The radiances can be assimilated under all conditions with the state-ofthe science NWP models Advanced JCSDA community-based radiative transfer model, Advanced data thinning techniques AIRS, ATMS, Cr. IS, VIIRS, IASI, SSM/IS, AMSR, WINDSAT, GPS , more products assimilated The radiances from advanced sounders will be used. Cloudy radiances will be tested under rain-free atmospheres, more products (ozone, water vapor winds) A beta version of JCSDA community-based radiative transfer model (CRTM) transfer model will be developed, including nonraining clouds, snow and sea ice surface conditions Improved JCSDA data assimilation science AMSU, HIRS, SSM/I, Quikscat, AVHRR, TMI, GOES assimilated The CRTM include cloud, precipitation, scattering The radiances of satellite sounding channels were assimilated into EMC global model under only clear atmospheric conditions. Some satellite surface products (SST, GVI and snow cover, wind) were used in EMC models Radiative transfer model, OPTRAN, ocean microwave emissivity, microwave land emissivity model, and GFS data assimilation system were developed Pre-JCSDA data assimilation science 17 2002 2003 2004 2005 2006 2007 2008 2009 2010
Some Major Accomplishments • • • Common assimilation infrastructure at NOAA and NASA Common NOAA/NASA land data assimilation system Interfaces between JCSDA models and external researchers Community radiative transfer model-Significant new developments, New release June 2005 Snow/sea ice emissivity model – permits 300% increase in sounding data usage over high latitudes – improved polar forecasts – May 2005 Impact studies of POES AMSU, Quikscat, GOES and EOS AIRS/MODIS with JCSDA data assimilation systems completed Advanced satellite data systems such as EOS (MODIS Winds, Aqua AIRS, AMSR-E) tested for implementation -MODIS winds, polar regions - improved forecasts. Current Implementation -Aqua AIRS - improved forecasts. (Implemented May 2005) Improved physically based SST analysis – operational testing Advanced satellite data systems such as DMSP (SSMIS), CHAMP GPS being tested for implementation. Upcoming implementation of new selection procedure for AIRS data and addition of MODIS winds (Oct 25, 2005) 18 Preparing for GPS/COSMIC
AIRS data coverage at 06 UTC on 31 January 2004. (Obs-Calc. Brightness 19 Temperatures at 661. 8 cm-1 are shown)
CURRENT SATELLITE DATA STATUS AIRS v 1. Implemented MAY 2005 AIRS v 2. Completed Operational Trial - NCO MODIS Winds Completed Operational Trial - NCO NOAA-18 AMSU-A Completed Operational Trial - NCO NOAA-18 MHS Completed Operational Trial - NCO NOAA-17 SBUV Total Ozone Completed Operational Trial - NCO NOAA-17 SBUV Ozone Profile Completed Operational Trial - NCO SSM/I Radiances Operational Trial with GSI compl. ( prod. now used) COSMIC/CHAMP Testing Assim. System SSMIS Quality Control and Data Selection being Finalized MODIS Winds v 2. RT Testing WINDSAT Wind Vector Assimilation - Active AMSR/E – Radiance Assimilation Test and Development AIRS/MODIS Sounding Channels Assim. Data in Preparation GOES – SW Winds To be Tested GOES Hourly Winds To be Tested GOES 11 and 12 Clear Sky Rad. Assim(6. 7µm) To be Tested MTSAT 1 R Wind Assim. Data in Preparation AURA OMI Test and Development TOPEX, JASON 1, ERS-2 ENVISAT ALTIMETER Test and Development, Ops 06 GODAS FY – 2 C Data in Preparation Implementation scheduled for Oct 25, 2005 20
AIRS Data Usage per Six Hourly Analysis Cycle with Oct 25 Implementation Number of AIRS Channels Data Category Total Data Utilized by Analysis ~200 x 106 radiances (channels) Data Selected for Possible Use ~2. 1 x 106 radiances (channels) Data Used in 3 D VAR Analysis(Clear Radiances) ~0. 85 x 106 radiances (channels) 21
Operational prior to Oct 25 Operational on Oct 25 22
Operational prior to Oct 25 Operational on Oct 25 23
Summary • Balance is needed among observations, modeling and computational power • Dependence on Global Observing System for all predictions • The Global Observing System is increasingly dominated by satellite observations • Getting ready for NPOESS: must prepare for – – – Increased data accuracy (high spectral resolution) Increased volume of data Improved CAL/VAL process to insure accelerated use of data Sustaining the timeliness of operations Improved data assimilation and model prediction systems to ingest and use all satellite data in real time for a total Earth System • To be ready for NPOESS: A successful JCSDA 24
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