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COMET Satellite Meteorology Course April 3-13, 2000

COMET Satellite Meteorology Course April 3-13, 2000 Satellite Applications for Numerical Weather Prediction Bob Aune NOAA/NESDIS/ORA/ARAD/ASPT Cooperative Institute for Meteorological Studies (CIMSS) Madison, Wisconsin. Eta Analysis/Forecast Sensitivity

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COMET Satellite Meteorology Course April 3-13, 2000

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  1. COMET Satellite Meteorology Course April 3-13, 2000 Satellite Applications for Numerical Weather Prediction Bob Aune NOAA/NESDIS/ORA/ARAD/ASPT Cooperative Institute for Meteorological Studies (CIMSS) Madison, Wisconsin

  2. Eta Analysis/Forecast Sensitivity SSM/I, GOES Sounder, TOVS, GOES winds RAOB, ACARS GOES Data in Mesoscale Models 3-layer Precipitable Water Cloud Initialization Cloud-track/Water Vapor Winds Future Platforms Advanced Baseline Imager Advanced Baseline Sounder Observing System Simulation Experiments (OSSE)

  3. Impact of Five Satellite Data Types in the Eta Data Assimilation System during Three Seasons by Tom H. Zapotocny 1 W. Paul Menzel 1,2 James P. Nelson III 1 and James A. Jung 1 1 Cooperative Institute for Meteorological Satellite Studies 2 National Environmental Satellite, Data, and Information Service

  4. Measure of 00-hr sensitivity and 24-hr forecast impact of five satellite data types assimilated into the EDAS for multi-day time periods covering three seasons (616 simulations). Data types examined are: • Special Sensor Microwave/Imager marine total PW (SSM/I) • GOES sounder marine three layer PW (GOESM) • TOVS marine cloudy temperature soundings (TOVCD) • GOES marine high-density cloud drift winds (GOESC) • GOES marine cloud top water vapor winds (GOESW) • Sensitivity and forecast impact of rawinsonde and aircraft • data is also evaluated.

  5. The following time periods were studied: • 13-23 December 1998, 10-20 April 1999, 13-23 July 1999. • NCEP 80 km parallel runs were used for background. • EDAS was run at 80 km horizontal resolution and 38 levels vertically. • The data type being denied was unavailable to 3DVAR for the entire 11-day time period.

  6. Evaluation criteria where D is the denied run, C is the control run, and A is the validating analysis A positive forecast impact means the simulation was better with the particular satellite data included.

  7. Errors assigned to observations in the EDAS at five pressure levels. The data type, description and units are shown at left. Rawinsonde and ACAR temperature (RAOB1, ACAR1) and wind (RAOB2, ACAR2) errors are also included. • ID Type 1000 850 700 500 300 (hPa) • RAOB1 Temp (K) 1.2 0.8 0.8 0.8 0.9 • ACAR1 Temp (K) 1.5 1.1 1.0 1.0 1.0 • RAOB1 Sp Hum (%) 5.0 7.0 10.0 20.0 20.0 • TOVCD (M) Temp (K) 7.6 7.1 6.6 6.6 7.0 • SSM/I (M) PW (mm) 8.0 8.0 8.0 8.0 8.0 • GOESM (M) PW (mm) 8.0 8.0 8.0 8.0 8.0 • RAOB2 Wind (m/s) 1.4 1.5 1.6 2.1 3.0 • ACAR2 Wind (m/s)2.5 2.5 2.5 2.5 2.5 • GOESC (MC) Wind (m/s) 1.8 1.8 1.9 2.1 3.0 • GOESW (MC) Wind (m/s) 1.8 1.8 1.9 2.1 3.0 • M - Marine only C - Cloud only

  8. Sat data impact on RH forecast in three seasons Dec Apr Jul

  9. Sat data impact on T forecast in three seasons Dec Apr Jul

  10. sat 00 24 Z T U RH

  11. no-sat 24 00 Z T U RH

  12. no-sat sat Z T U RH

  13. Summary of Sat Impact on T and RH forecast for all three seasons

  14. Conclusions Large impact at 00-hr is largely reduced at 24-hr for sat and non-sat data alike Each data type influences fields they do not observe as much as ones they do (eg. U affects RH) Overall modest positive forecast impact from all five sat data types during all three seasons; only 28 / 295 forecasts negative impact Cloud motion winds have most positive forecast impact overall especially during the winter season. Precipitable water has largest positive forecast impact during the summer and transition seasons. During the summer season sat data provides as much or slightly more positive impact at 24-hrs than non-sat data.

  15. Eta Analysis/Forecast Sensitivity SSM/I, GOES Sounder, TOVS, GOES winds RAOB, ACARS GOES Data in Mesoscale Models 3-layer Precipitable Water Cloud Initialization Cloud-track/Water Vapor Winds Future Platforms Advanced Baseline Imager Advanced Baseline Sounder Observing System Simulation Experiments (OSSE)

  16. EDAS/Eta Parallel Runs • Operational GOES retrievals used • 5x5 field-of-view • 3-layers of PW (over land and water) • 5 inserts (every 3 hours) • 80 km • 38 levels • “fully-cycled” • 2 weeks out of the 10 months listed

  17. What’s the Equitable Threat Score (ETS)? (Hits - E) (Hits + Misses + False Alarms + E) # Forecast points x # Observed points # of Total points possible ETS = E = Rogers et al, Sept. 1996, Weather and Forecasting

  18. In comparing to US raingauges, overall, the inclusion of GOES PW improves Eta precipitation forecasts. (This improvement is on the order-of-magnitude as the yearly historical average (‘87-’97)).

  19. GOES Sounder Precipitable Water vapor (PW) Cumulative Equitable Threat Scores by forecast time. The months represented are: October, November, December-1998, January, April, May, June, July, August and September-1999. There are approximately 150,000 total points for each forecast time. Forecast time (Analysis times) Improvement 00 - 24 h (12 UTC runs) 2.2% 12 - 36 h (00 UTC runs) 2.5% 24 - 48 h (12 UTC runs) 2.0%

  20. In the winter, the GOES PW only slightly improves precipitation forecasts

  21. In the summer, the GOES PW makes a more substantial improvement to the precipitation forecasts

  22. Threat Bias

  23. GOES Sounder cloud information can be used to improve regional models. - CRAS - RUC-II - Eta/EDAS Only the sounders have multiple CO2 channels. ABI has only one such channel.

  24. GOES-8/10 Sounder Cloud Data in NWP: Research • Cloud information used in CIMSS Regional Assimilation System (CRAS) over both land and ocean. • MAPS-2 is using hourly cloud-top information in continuous real-time cloud analysis experiments. • Experiments with the NCEP Eta system have begun.

  25. NOWCASTING/FORECASTING APPLICATIONS 600 hPa 300 hPa • Combining both images can locate deep convection and major weather systems • Thin clouds imply regions of radiational cooling 50% 98%

  26. 3-hour forecast: No Sounder data Coverage: CTP and TPW 3-hour forecast: With Sounder data Observed GOES-9 Sounder Image More realistic moisture forecasts with GOES sounder data.

  27. 3-hour forecast: No Sounder data Coverage: CTP and TPW 3-hour forecast: With Sounder data Observed GOES-9 Sounder Image More realistic moisture forecasts with GOES sounder data.

  28. GOES CLOUD/PW DATA & NWP MODELS (CRAS) 24 hr Forecast w/o Sat CTP & PW GOES-8 11m Image • The NWP model is initialized with Sat. CTP & PW • Prior to start of forecast, Sat. CTP is inserted at 3 hourly intervals • With Sat. data positive impact is seen over the eastern Pacific and central part of US 24 hr Forecast w Sat CTP & PW

  29. GOES CLOUD/PW DATA & NWP MODELS (CRAS) GOES-8/10 7m Image 24 hour CRAS Forecast w Sat CTP & PW • The NWP model is initialized with Sat. CTP & PW • Prior to start of forecast, Sat. CTP is inserted at 3 hourly intervals • General water vapor structure is preserved

  30. 00 UTC 23 March 1999 GOES Sounder-Derived plus Model-Derived Cloud Top Pressure GOES CLOUD PRODUCT & NWP MODELS (RUC) Impact of the GOES Sounder-Derived Cloud Product (Gray to Black indicate cloud added; Yellow to Red indicate cloud removed by GOES data) • Upper level relative humidity is improved for forecasts with cloud data

  31. CURRENT STATUS of GOES SOUNDER CLOUDS and the EDAS/ETA James Jung1 1Cooperative Institute for Meteorological Satellite Studies (CIMSS) UW-Madison

  32. GOES Sounder Cloud Experiments • Consistent treatment of the Saturation Specific Humidity with respect to ice in 3dvar. (This is extremely important to limit the over-prediction of clouds.) • Cloud initiation threshold changed from 75%/85% for land/ocean to 97% everywhere. • Cloud Water Mass added and removed as required from the GOES Sounder cloud product. • Bogus Specific Humidity Observations derived to keep clouds in/out where necessary. Control: with sat spec humidity fix, 75/85% cloud threshold Experiment: with sat spec humidity fix, 97% cloud threshold, add/remove cloud, and add/remove specific humidity as necessary

  33. Analysis -- High Clouds Control Experiment Sounder Clouds High Clear Low Mid

  34. Analysis -- Low Clouds Control Experiment Sounder Clouds

  35. 12-hour forecast -- High Clouds Control Experiment Sounder Clouds

  36. 12-hour forecast -- Low Clouds Control Experiment Sounder Clouds Clear

  37. Eta 1-hr cloud forecasts -- Control (with Saturation Specific Humidity fix) 99157 01 - 06 UTC

  38. Sounder 1-hr clouds 99157 01 - 06 UTC

  39. Eta Analysis/Forecast Sensitivity SSM/I, GOES Sounder, TOVS, GOES winds RAOB, ACARS GOES Data in Mesoscale Models 3-layer Precipitable Water Cloud Initialization Cloud-track/Water Vapor Winds Future Platforms Advanced Baseline Imager Advanced Baseline Sounder Observing System Simulation Experiments (OSSE)

  40. NATIONAL POLAR-ORBITING OPERATIONAL ENVIRONMENTAL SATELLITE SYSTEM VIIRS GPSOS CMIS SARSAT SES TSIS DCS ALT OLS SSMIS SESS MOLS SSMIS SESS AVHRR IASI SEM AMSU-A MHS GOME SARSAT DCS ASCATT MODIS MISR CERES(2) MOPITT ASTER AVHRR HIRS AMSU-A MHS SBUV SEM SARSAT DCS VIIRS CrIS ATMS CERES (TBD) VIIRS GPSOS CMIS CrIS SES ATMS DCS OMPS CERES MODIS AIRS CERES(2) AMSU-A AMSR HSB SatelliteTransition DMSP DMSP

  41. ABI/ABS Information Timothy J. Schmit, W. P. Menzel, Robert M. Aune NOAA/NESDIS/ORA Advanced Satellite Products Team (ASPT) Allen Huang, Gail Bayler, Mat Gunshor,Jonathan Thom Cooperative Institute for Meteorological Satellite Studies (CIMSS) Madison, Wisconsin UW-Madison

  42. Information content (independent information using global covariance) analysis of the current GOES sounder, ABI and the ABS. A larger number denotes more information. The ‘extended’ ABI does not even come close to giving the information content of the current sounder, much less the next generation sounders.

  43. For any number of parameters, an extended ABI is no replacement for even the current sounder. Smaller values denote more retrieval skill.

  44. Geo-Interferometer nears Raob-like depiction of atmosphere Analysis of NOAA global raob data (tropics and mid-lat summer) VAS - past GOES - current G18 - 18 1/2cm-1 chs G50 - 50 1/2cm-1 chs GAS - ABS 2000+ 1/2cm-1 chs RAOB - T to 150mb (Q to 300mb)

  45. Only the ABS gives the needed (in year 2008) temperature accuracy of less than 1.0 K.

  46. Only the ABS gives the needed (in year 2008) moisture accuracy of less than 20%.

  47. IMG demonstrates interferometer capability to detect low level inversions: example over Ontario with inversion (absorption line BTs warmer) and Texas without (abs line BTs colder)

  48. Water Vapor Structure for Tracking This field of Relative Humidity was derived from interferometric data. NAST-I September 14, 1998 CAMEX-3 Altitude, km 00:32 00:36 00:41 UTC 125 km Relative Humidity, %

  49. GIFTS Simulation of Hurricane Bonnie: Winds from Water Vapor Retrieval Tracking Higher spectral resolution means more levels of winds can be determined.

  50. Preliminary Findings for the Geo-Interferometer Observing System Simulation Experiment (OSSE) at CIMSS CIMSS/OSSE Team : Bob Aune ; Paul Menzel ; Jonathan Thom ; Gail Bayler ; Chris Velden ; Tim Olander ; and Allen Huang Cooperative Institute for Meteorological Satellite Studies University of Wisconsin September 1999

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