lemarshall jcsda COSMICRs

Slide1: 

COSMIC Retreat

Overview: 

Overview Background Define JCSDA Mission, Vision and Goals Progress, Major Accomplishments Recent Advances GPS/COSMIC Program Summary

JCSDA Mission and Vision: 

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

Goals – Short/Medium Term: 

Goals – Short/Medium Term Increase uses of current and future satellite data in Numerical Weather and Climate Analysis and Prediction models Develop the hardware/software systems needed to assimilate data from the advanced satellite sensors Advance the common NWP models and data assimilation infrastructure Develop common fast radiative transfer system Assess the impacts of data from advanced satellite sensors on weather and climate analysis and prediction Reduce the average time for operational implementations of new satellite technology from two years to one

Goals – Longer Term: 

Goals – Longer Term Provide the “bridge” for the integrated use of GEOSS data within numerical models Develop the tools for effective integration of GEOSS observations into environmental models Expand assimilation system to provide input to models of: environmental hazards air and water quality and resources terrestrial, coastal, and marine ecosystems climate variability and change agricultural productivity energy resources human health biodiversity

JCSDA’s Role in Satellite Program Developments : 

JCSDA’s Role in Satellite Program Developments Definition of scientific and operational requirements for new instruments CRTM forward and adjoint model development Observation system simulation experiments (OSSE’s) Involvement in instrument CALVAL Error characterization of instrument observations Quality assurance and forward model refinement (tuning) Data assimilation and numerical model testing Analysis of impact on analyses and forecasts Delivery and transfer of improved forecast system to the operational communities Involvement in the end to end process

Slide7: 

The Challenge Satellite Systems/Global Measurements Aqua Terra TRMM SORCE SeaWiFS Aura Meteor/ SAGE GRACE ICESat Cloudsat Jason CALIPSO GIFTS TOPEX Landsat NOAA/POES GOES-R WindSAT NPP COSMIC/GPS SSMIS NPOESS

Satellite Instrument Data Base: 

Satellite Instrument Data Base

Slide9: 

NPOESS Satellite CMIS- μwave imager VIIRS- vis/IR imager CrIS- IR sounder ATMS- μwave sounder OMPS- ozone GPSOS- GPS occultation ADCS- data collection SESS- space environment APS- aerosol polarimeter SARSAT - search & rescue TSIS- solar irradiance ERBS- Earth radiation budget ALT- altimeter SS- survivability monitor CMIS VIIRS CrIS ATMS ERBS OMPS

 5-Order Magnitude Increase in Satellite Data Over 10 Years : 

5-Order Magnitude Increase in Satellite Data Over 10 Years Year Count (Millions) Daily Upper Air Observation Count Year Satellite Instruments by Platform Count NPOESS METEOP NOAA Windsat GOES DMSP 1990 2010 2000 1990 2010 2010-250ch Year 2002 2003

Satellite Data used in NWP: 

Satellite Data used in NWP HIRS sounder radiances AMSU-A sounder radiances AMSU-B sounder radiances GOES sounder radiances GOES, Meteosat, GMS winds GOES precipitation rate SSM/I precipitation rates TRMM precipitation rates SSM/I ocean surface wind speeds 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 Altimeter sea level observations (ocean data assimilation) Current Upgrade adds; AIRS, MODIS Winds…

JCSDA Road Map (2002 – 2010): 

JCSDA Road Map (2002 – 2010)

JCSDA Road Map (2002 - 2010): 

JCSDA Road Map (2002 - 2010) Improved JCSDA data assimilation science 2002 2004 2007 2008 2009 2005 OK Required 2003 Advanced JCSDA community-based radiative transfer model, Advanced data thinning techniques Science Advance By 2010, a numerical weather prediction community will be empowered to effectively assimilate increasing amounts of advanced satellite observations 2010 AMSU, HIRS, SSM/I, Quikscat, AVHRR, TMI, GOES assimilated AIRS, ATMS, CrIS, VIIRS, IASI, SSMIS, AMSR,WINDSAT,CHAMP COSMIC,products assimilated Pre-JCSDA data assimilation science Radiative transfer model, OPTRAN, ocean microwave emissivity, microwave land emissivity model, and GFS data assimilation system were developed 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 A beta version of JCSDA community-based radiative transfer model (CRTM) transfer model will be developed, including non-raining clouds, snow and sea ice surface conditions The radiances from advanced sounders will be used. Cloudy radiances will be tested under rain-free atmospheres, more products (ozone, water vapor winds) NPOESS sensors ( CMIS, ATMS…) GIFTS, GOES-R The CRTM include cloud, precipitation, scattering The radiances can be assimilated under all conditions with the state-of-the science NWP models Resources:

Short Term Priorities 04/05: 

Short Term Priorities 04/05 SSMIS: Collaborate with the SSMIS CALVAL Team to jointly help assess SSMIS data. Accelerate assimilation into operational model as appropriate MODIS: MODIS AMV assessment and enhancement. Accelerate assimilation into operational model. AIRS: Improved utilization of AIRS Reduce operational assimilation time penalty (Transmittance Upgrade) Improve data coverage of assimilated data. Improve spectral content in assimilated data. Improve QC using other satellite data (e.g. MODIS, AMSU) Investigate using cloudy scene radiances and cloud clearing options Improve RT Ozone estimates

Short Term Priorities 05/06: 

Short Term Priorities 05/06 SSMIS: Collaborate with the SSMIS CALVAL Team to jointly help assess SSMIS data. Accelerate assimilation into operational model as appropriate GPS: GPS (CHAMP) assimilation and assessment. Accelerate GPS (COSMIC) assimilation into operational model. WINDSAT: Assimilation and assessment. IASI: Complete preparations for METOP/IASI Complete Community RTM transmittance preparation for IASI Assimilate synthetic IASI BUFR radiances in preparation for METOP.

Major Accomplishments: 

Major Accomplishments Common assimilation infrastructure at NOAA and NASA Community radiative transfer model Common NOAA/NASA land data assimilation system Interfaces between JCSDA models and external researchers Snow/sea ice emissivity model – permits 300% increase in sounding data usage over high latitudes – improved polar forecasts MODIS winds, polar regions - improved forecasts Improved physically based SST analysis Advanced satellite data systems such as DMSP (SSMIS), CHAMP GPS data and EOS (MODIS Winds, Aqua AIRS, AMSR-E) being tested for implementation Impact studies of POES AMSU, Quikscat, GOES and EOS AIRS/MODIS… with GMAO/NCEP data assimilation system

Slide17: 

JCSDA RECENT ADVANCES

Slide18: 

Figure 3. Latest optical path of gaseous transmittance model performed at 19 HIRS channels

Slide19: 

Figure 4. Impact of sea ice and snow emissivity models on the GFS 24 hr. fcst. at 850hPa. (1 Jan. – 15 Feb. 2004); the pink curve shows theACC with new snow and sea ice emissivity models

Slide20: 

Figure 7. Impact of MODIS AMVs on the operational GFS forecast at 500hPa (60°S - 90°S). (10 Aug. – 23 Sept. 2004); the pink (dashed) curve shows the ACC with (without) MODIS AMVs

Slide22: 

AIRS Data Assimilation J. Le Marshall, J. Jung, J. Derber, R. Treadon, S.J. Lord, M. Goldberg, W. Wolf and H-S Liu, J. Joiner, and J Woollen…… 1-27 January 2004 Used operational GFS system as Control Used Operational GFS system Plus Enhanced AIRS Processing as Experimental System

Slide23: 

Figure 5.Spectral locations for 324 AIRS thinned channel data distributed to NWP centers.

Slide24: 

Table 2: AIRS Data Usage per Six Hourly Analysis Cycle

Slide25: 

Figure 1(b). 500hPa Z Anomaly Correlations for the GFS with (Ops.+AIRS) and without (Ops.) AIRS data, Southern hemisphere, January 2004

Slide26: 

Figure 3(b). 500hPa Z Anomaly Correlations for the GFS with (Ops.+AIRS) and without (Ops.) AIRS data, Northern hemisphere, January 2004

Assimilation of GPS RO observations at JCSDA: 

Assimilation of GPS RO observations at JCSDA Lidia Cucurull, John Derber, Russ Treadon, Martin Bohman, Jim Yeo…

Motivation: 

Motivation To develop the total infrastructure (codes, scripts, etc.) necessary to monitor and assimilate radio-occultation (RO) observations by JCSDA partners and the wider community. Work schedule enables complete preparation of JCSDA data assimilation system in time for COSMIC launch (estimated Dec 2005 or Jan 2006).

Slide29: 

GPS - CHAMP/COSMIC Non linear operator implemented in GSI 3D Var. Error characterization well advanced CHAMP observation tests ongoing, including study of CHAMP use with complementary data. Study of CHAMP/COSMIC logistics for RT application underway

Slide30: 

GPS - CHAMP/COSMIC Assessment of Refractivity vs Bending Angle approaches Assessment of Local vs Non-Local approaches

Slide31: 

CHAMP data flow to JCSDA This system is currently under development by UCAR & JCSDA

Slide32: 

CHAMP NRT END TO END/ASSIM TEST March 2005 BUFR encoding software complete NCEP BUFR software complete OSDPD agreement written Test data tanks to be formed Prelim assim code complete GFZ/DWD to be further engaged

Slide33: 

COSMIC data flow to Weather Centers This system is currently under development by UCAR, NESDIS, & UKMO

Slide34: 

COSMIC END TO END/ASSIM TEST July 2005 BUFR encoding software complete NCEP BUFR software complete OSDPD agreement written NCO to be engaged/Test data tanks to be formed Prelim assim code complete GFZ/DWD to be kept engaged

CY 2004 Activity: 

CY 2004 Activity Implementation of the local refractivity operator in the (new NCEP) Gridpoint Statistical Interpolation (GSI) analysis system. Improvement of the Forward Operator . Ability to ingest refractivity profiles in the system. Compute the innovation vector with CHAMP data (Forward Model). Tangent Linear and Adjoint codes (implemented and tested with the improved Forward Operator). Impact studies using single observation and single profile of refractivity. Impact studies of the assimilation of all profiles available at a given analysis time. Account for the different vertical resolution between observations and model. Implementation of QC checks in the code.

6hr Window Profiles Assimilation: 

6hr Window Profiles Assimilation Analysis Time: 2002080812 (46 CHAMP profiles) Observations of refractivity rejected if (O-B)/error(O) > 10 Deviate more than 5% from background below 5 km (and if so, also remove observations below this altitude).

Assimilation well behaved: 

Assimilation well behaved The analysis fits the data better after each iteration Some data rejected at first, get into the system in later iterations. 1st iteration Bias: 0.0021 rms: 0.0133 2nd iteration Bias: 0.0010 rms: 0.0090 3rd iteration Bias: 0.0010 rms: 0.0089

Outlook for CY 2005: 

Outlook for CY 2005 (1) QC Test and implement additional QC checks (in lower troposphere, stratosphere, to account for superrefraction) (2) Error Better characterization of the refractivity (measurement) errors Examine representativeness error. Adjustment of the background error covariance matrix according to the results of the assimilation of profiles of refractivity. (3) Experiments Conduct a cycling experiment for one month period to assess the impact of the assimilation of the CHAMP RO profiles to get ready for COSMIC. (4) Forward Operators Implementation of the bending profile Forward Operator. (As the bending angle observations are less contaminated by the climatological guess field, a better performance in the assimilation system is expected. (5) Pass CHAMP data in COSMIC format from CDAAC through OSDPD to JSCDA/NCEP for assimilation studies.

Note: 

Note Preparations require community support Data access required early Staff stability

Prologue: 

Prologue JCSDA well positioned to exploit the COSMIC Program in terms of: Assimilation science Modeling science. Computing power Generally the next decade of the meteorological satellite program promises to be every bit as exciting as the first, given the opportunities provided by new observations, modern data assimilation techniques, improving environmental modeling capacity and burgeoning computer power. The Joint Center will play a key role in enabling the use of advanced satellite data such as RO data, from both current and future advanced systems, for environmental modeling. USA Inc. and the Global Community will be a significant beneficiary from the Centers activity.