JCSDA Observation System Simulation Experiments (OSSE) Plan for GOES-R Series Sounding Mission

1. JCSDA Observation System Simulation Experiments (OSSE) Plan for GOES-R Series Sounding Mission Extracted From draft presentation Fuzhong Weng, STAR/SMCD Stephen Lord, NCEP/EMC Lars Peter Riishojgaard, NASA/GMAO ****** 2007

2. Project Objectives: • Use Full OSSEs as a Quantitative Tool for Observing System design and planning • OSSEs integrate new instruments into Data Assimilation System, thereby providing complete preparation for their use (JCSDA goal) • Apply OSSE system to GOES-R and other advanced instrument candidates to demonstrate the potential added value of • High resolution of vertical temperature and moisture structures from GOES-R hyperspectral infrared soundings for regional forecasting (e.g. flash flood and convection) • Atmospheric wind products (e.g. GOES-R infrared cloud and water vapor winds) versus a direct wind measurement • Geostationary microwave sounder

3. JCSDA OSSE Partnership • Interagency • NCEP, STAR, NASA (GMAO, GLA, SIVO), ESRL collaboration • 10 years of experience • International Effort • ECMWF, KNMI joined Joint OSSE studies last 2 years • European and Asian community interests growing • Universities and NESDIS Corporative Institutes • UWISC/CIMSS (mesoscale OSSE) • CSU/CIRA (mesocale OSSE) • MSU/GRI • Univ. of Utah • Initial Focus • Global forecast impacts of HES • HES regional impacts on hurricane and high-impact weather events

4. Remark • Severe weather cases don’t have to be local to US in OSSEs. We can make GOES-R sounder data anywhere on the planet (one of the nice things about OSSEs). • While the hypothesis is that Geo IR soundings can improve prediction of severe weather events, one must not prejudge the result. Many have doubts as you might know. • Better stated as a hypothesis: “what type of observation(s) will improve the prediction of severe wx events? • Much fine resolution data will produce a larger scale impact by Super-Obbing effect.

5. Specific Events for GOES-R OSSE • GOES-R Series Sounder: Improve prediction of severe storms • GOES-R OSSE must • realistically simulate pre-convection environments (moisture features) • resolve cloud and precip structures • produce adequate temporal/spatial sampling

6. Work Plan: Phase I • Preparation of Nature Runs • Low Res Joint OSSE Global NR: 13 month T511 (ECMWF) • High Res Joint OSSE Global NR: two 5 week T799 (ECMWF) • Regional: CSU/RAMS (Candidate) • Super high res Global NR • Validation of Nature Runs • Temperature/moisture/wind • Cloud coverage: GOES imagery vs.simulations • Cloud liquid/ice statistics: Cloudsat/Calipso vs. Simulations • Initial OSSE • Experiment demonstrating the assimilation of modeled temperature and humidity fields extracted from the Nature Run

7. Work Plan: Joint OSSE Nature Runs • Joint OSSE T511 Nature Run • Produced by ECMWF • Equivalent approximately 25km grid point model • 40 km resolution in physics • 91 vertical layers • 3 hourly output from May 2005 to June 2006 integration • Realistic extratropical storm frequency and statistics, hurricane and tropical waves • Improved cloud • Suitable for global OSSEs • Joint OSSE T799 Nature Run • Produced by ECMWF • Equivalent approximately 15km grid point model • 25 km resolution in physics • 91 vertical layers • Hourly outputs for two 35day periods • Better hurricane and severe storm seasons • Suitable for most mesoscale OSSEs and to test synoptic and mesoscale impacts of GOES-R Lifespan distribution of extratropical cyclones during February 2006 in Northern Hemisphere. Red bars are for NR. Green bars are for NCEP analysis

8. Need for higher resolution Nature Run • Need for a Nature Run with higher resolution mesoscale OSSEs • Hurricanes, lake snow effects, severe storms • Less than 5km model (without cloud parameterization) • Frequency of output : 5min • Candidates • Global cloud resolving model • GFDL-ESRL (Planned delivery time 2012) • NICAM • Local high resolution global model • Using Fibonacci grid • Nested regional model • CSU RAMS (regional atmospheric modeling system) • RUC • WRF

9. Work Plan: Possibility for Regional OSSEs • Possibilities for Regional Nature run • Performance of high resolution regional models needs to be evaluated • Noise from boundary conditions must be evaluated • A 5 day Nature Run with resolution of 1-4 km and 500x500x35 • Possibly using the RAMS model (Other candidates: RUC, WRF and more) • Waiting for a Global high resolution model is a possibility • Validation of Regional Nature Run • A major challenge • Nature Run must produce statistically representative atmospheric state • Major validation effort needed • Cloud coverage: GOES imagery vs. Simulations • Cloud liquid/ice statistics: Cloudsat/Calipso vs. Simulation • Adequate regional data assimilation system beyond current state of science • Non-hydrostatic atmosphere • Analysis balance constraints • Time dependency (4D-Var) still under development • “5-year” development??

10. Work Plan: Phase II • Conducting the OSSE • Complete validation for ECMWF Nature Run • Construct • Conventional observations • RAOB, Air Craft, Cloud Track Wind • Satellite radiances for all existing instruments • AQUA, IASI, ASCAT • Observations from future instruments • Radiances AND • Retrieved temperature and humidity profiles • Observation errors generated by the retrieval method • Doppler Wind Lidar • Calibration process • Demonstrate impact of known instruments is statistically comparable in both Real and Nature Run worlds