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Current status of AMSR-E data utilization in JMA/NWP

Current status of AMSR-E data utilization in JMA/NWP. Masahiro KAZUMORI Numerical Prediction Division Japan Meteorological Agency. 14-16 July 2008. Joint AMSR Science Team Meeting, Telluride, CO. Contents. Utilizations of AMSR-E data in JMA/NWP Assimilation

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Current status of AMSR-E data utilization in JMA/NWP

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  1. Current status of AMSR-E data utilization in JMA/NWP Masahiro KAZUMORI Numerical Prediction Division Japan Meteorological Agency 14-16 July 2008 Joint AMSR Science Team Meeting, Telluride, CO

  2. Contents • Utilizations of AMSR-E data in JMA/NWP • Assimilation • Radiance assimilation for Global model (GSM) • Retrieval (TPW, Rain rate) assimilations for Mesoscale Model (MSM) • Verification of the forecast models • Total Precipitable Water • Monthly Rainfall • Heavy rain and typhoon case study • Case study : Cyclone Nargis in Myanmar 2008 • Impact of MW-Imager data in JMA operational system • Use of all weather wind speed from AMSR-E (on going development) Joint AMSR Science Team Meeting, Telluride, CO

  3. JMA/NWP models 20kmGSM Observation Joint AMSR Science Team Meeting, Telluride, CO

  4. Global Analysis Global Analysis TRMM TRMM use MWR radiance no MWR radiance difference difference Utilization of MW Imager data in GSM Assimilation of Microwave Radiometer (MWR) radiances from DMSP/SSMI, TRMM/TMI and Aqua/AMSR-E Less cloud-affected radiances over the ocean with SST > 5 deg.C Only vertical polarized channels at 19 – 89 GHz( to obtain moisture information) VarBCcorrects biases against analysis Impacts on analyses/forecasts Better TPW (Total Precipitable Water) analysis verified against TRMM retrieved TPW Better precipitation forecasts: larger correlation between 1-day-forecast and GPCP (0.881=>0.891 for Aug2004) Better typhoon track forecasts Time sequence of TPW RMSE and bias between analysis and TRMM retrieval 5 May Start MWR radiance assimilation 25May Joint AMSR Science Team Meeting, Telluride, CO

  5. Conventional Data RA + MW TCPW &RR MWRs RR MWRs RR RA Obs. RA Obs. MWRs TCPW Utilization of MW Imager data in MSM Retrieval assimilation (Total Precipitable Water and Rain Rate from AMSR-E, TMI and SSMI) Impacts : Better rainfall forecasts • A case study : Fukui Heavy Rain in 2004 • “Assimilation of the Aqua/AMSR-E data to Numerical Weather Predictions”, Tauchi et al., IGARSS04 Poster Joint AMSR Science Team Meeting, Telluride, CO

  6. Verification : Total Precipitable Water Initial TPW 3-day Forecast Observation (AMSR-E) Forecast - Obs Monthly average for Aug. 2007 Initial -Obs GSM : Dry bias in deep convective area and wet bias along the ITCZ. The biases increase with forecast time. Satellite measurements reveal the numerical model biases. Joint AMSR Science Team Meeting, Telluride, CO

  7. Verification : Rainfall forecast GSM FT=24 AMSR-E RAIN GSM FT=72 Monthly Averaged R24 for Aug. 2007 Rainfall forecast in JMA Global Model is excessive, especially for deep convective area in the early stage of forecast. Satellite measurements are essential to evaluate the performance of JMA Global model and provide important information for further forecast model improvement. Joint AMSR Science Team Meeting, Telluride, CO

  8. FT=02 Jul. 12 15UTC init. FT=08 Jul. 12 09UTC init. FT=14 Jul. 12 03UTC init. Fake rain? Fake rains predicted in subsidence area of subtropics high were identified by comparison with AMSR-E measurement and indicate issues on current cumulus parameterization scheme in MSM. Verification : Heavy rain and typhoon MSM Rain forecast Valid time : 17 UTC July 12, 2007 Rain from AMSR-E Measurement MTSAT IR Image Joint AMSR Science Team Meeting, Telluride, CO

  9. Most of NWP centers predicted the cyclone landfall in Myanmar. But, the intensity of JMA forecast is weak. Case study: Cyclone Nargis in May 2008 Cyclone Nargis : Strong tropical cyclone made landfall in Myanmar on May 2, 2008 Forecast comparisons for several NWP centers(12UTC April 30, 2008 Initial forecast, Psea [hPa]) Observed cyclone track JMA ECMWF NCEP Day-1 Day-2 Joint AMSR Science Team Meeting, Telluride, CO

  10. JMA GSM Forecast (Rain and TPW) Psea [hPa] and Rain [mm/day] JMA GSM 12UTC April 30 Init. Psea and Rain24 TPW JMA/GSM Analysis In the Bengal bay, foregoing moisture flow from south west was well analyzed. The direction forecast of the cyclone was “eastward”. The JMA global forecast predicted the May 2 landfall. Day-1 Forecast Day-2 Forecast Joint AMSR Science Team Meeting, Telluride, CO

  11. Impact of MW-Imager data for TPW Initial Difference (W/ – W/O) Day-1 forecast diff (W/ – W/O) [mm] [mm] Data Coverage (MW-Imager) O-B [K] Case Study: W/: Same data usage as operational W/O : Without all MW Imager data in the analysis Rain affected data MW-Imager data (SSMI radiance) enhanced the moisture flow from south west and the impacts was retained for 24-hour TPW forecast. However, rain affected data were not used. Joint AMSR Science Team Meeting, Telluride, CO

  12. Use of all weather wind speed from AMSR-E • JAXA’s research products developed by Dr. Shibata and Mr. Saitoh. • Ocean surface wind speed retrievals under all weather condition using AMSR-E low frequency channels. • JMA developed a QC scheme for the data assimilation in JMA global 4D-Var system and started to study the impact on analysis and forecast. • Developed QC in JMA • Data selection (Above 7m/s) • Removal of land (and/or island) contaminated data. • Removal of sea ice contaminated data. • Thinning and averaging with 100km grid boxes. • Gross error check based on wind speed O-B. Joint AMSR Science Team Meeting, Telluride, CO

  13. AMSR-E all weather wind speed data All weather wind data JAXA L2 wind speed Averaging with 100km grid boxes 06UTC 29 April, 2008 Strong winds in the cyclone core are available. Need to make average with grid boxes to reduce noise and fit to model resolution (4D-Var :Inner model res. 80km). Joint AMSR Science Team Meeting, Telluride, CO

  14. The first analysis increment Used data Psea (W AMSR-E) Psea (W/O AMSR-E) Increment of wind AMSR-E all weather wind speed data strengthen the intensity and the surface wind speed in the analysis. Joint AMSR Science Team Meeting, Telluride, CO

  15. JMA + AMSR-E Impacts on forecasts Forecast comparisons for several NWP centers(12UTC April 30, 2008 Initial forecast, Psea [hPa]) JMA ECMWF NCEP Day-1 Day-2 The intensity in forecast was also strengthened. Joint AMSR Science Team Meeting, Telluride, CO

  16. Impacts on forecasts Cyclone Nargis Forecast and Analysis Central Pressure Red: W AMSR-E, Green: W/O AMSR-E 16 cases for each Max wind No significant improvement in the track forecast AMSR-E all weather wind speed data strengthen the intensity and wind. Joint AMSR Science Team Meeting, Telluride, CO

  17. Conclusions • AMSR-E data has been utilizing in JMA operational NWP Assimilation • Clear radiance assimilation for GSM • Retrieval (TPW and Rain rate) assimilations for MSM AMSR-E provide much information on rain and moisture for NWP Model Verifications • Total Precipitable Water • Rain distribution • Heavy rain and typhoon study MW imager measurements (Rain and TPW) reveal the forecast model errors (bias and accuracy) and the results lead to further forecast model improvement (Cumulus parameterization scheme) • Case study : Cyclone Nargis in Myanmar 2008 MW-Imager data play important roles to provide moisture information in GSM Difficulty of cloud and rain affected radiance assimilation All weather wind speed data were investigated in JMA/NWP • Available under severe weather condition (e.g. Tropical cyclone) • Assimilation experiments • Strengthen the intensity and the max wind speed • No significant improvement in the track forecast • Valuable data to provide realistic observational information under severe weather condition Joint AMSR Science Team Meeting, Telluride, CO

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