1 / 17

An update of AMSR-E total precipitable water retrieval algorithm and the application for JMA NWP

An update of AMSR-E total precipitable water retrieval algorithm and the application for JMA NWP. Masahiro Kazumori Numerical Prediction Division Japan Meteorological Agency. Contents. Utilization of AMSR-E data in JMA NWP Update of TPW algorithm for AMSR-E

theresia
Download Presentation

An update of AMSR-E total precipitable water retrieval algorithm and the application for JMA NWP

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. An update of AMSR-E total precipitable water retrieval algorithmand the application for JMA NWP Masahiro Kazumori Numerical Prediction Division Japan Meteorological Agency

  2. Contents • Utilization of AMSR-E data in JMA NWP • Update of TPW algorithm for AMSR-E • TPW retrieval from SSMIS brightness temperature • Assimilation experiment of SSMIS TPW in JMA NWP • Summary and plan

  3. Operational NWP Models in JMA Meso-scale NWP model Disaster prevention information 8 times/day implementation 5km horizontal resolution 4D-Var Data AssimilationSystem • Global NWP model • One-week and short range forecast • 4 times/day implementation • 20km horizontal resolution • 4D-Var DataAssimilationsystem GSM MSM

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

  5. Recent updates of MSM DA system Introduction of a new 4D-Var data assimilation system based on Non hydrostatic model, JNoVA, on April 7, 2009 Improvements of rainfall, wind and temperature forecasts Comparison of 3-hr rainfall distribution for Typhoon case in 16 Aug. 2006. RA Obs. New (24-hr fcst.) Old (24-hr fcst.) 参考：配信資料に関する技術情報（気象編）第297号 • Changes • Horizontal resolution: from 10km to 5km • Number of vertical model layer: from 40 to 50. (Model Top: 22km) • Assimilation Time window: from 6-hour to 3-hour

  6. Impacts of MW data (TPW and Rain rate)on moisture analysis in MSM AMSR-E data Coverage(TPW O-B) Analysis Increment of TPW With MW data WO MW data Much increment from the assimilation of MW data. Satellite precipitation and moisture measurements are important data source in data sparse area (over ocean). 18UTC April 19, 2009

  7. AMSR-E Tr : Square of Transmittance Ta : Atmosphere : Emissivity Ts : Sea Surface • RT model : • Single-layer atmosphere and sea surface • Atmospheric transmittance is obtained from an • iteration calculation using T850 and LUT based on RAOB profiles • Dependencies of to SST and SSW are included in LUT TPW retrieval algorithm for AMSR-E TPW data are retrieved in the pre-process of the DA system Input : AMSR-E 19,23,37V and H pol. Brightness Temperature JAXA L1B Ancillary data AMSR-E L2 SST, SSW, T850 (JMA GANAL) • Original code was developed by Mr. Takeuchi at JMA (Takeuchi 2002). • TPW algorithm was adopted as standard algorithm for AMSR-E in JAXA • and also have been used in NWP at JMA Takeuchi, Y., “Algorithm theoretical basis document of the algorithm to derive total water vapor content from ADEOS-II/AMSR”, Special Issue on AMSR Retrieval Algorithms, EORC Bulletin/Technical Report, JAXA, 2002.

  8. Update of TPW algorithm for AMSR-E LUT in the algorithm was updated by using 3-yr RAOB and AMSR-E collocated dataset (2006-2008). Updated LUTs : T850 and Mean atmospheric temperature table Wind speed correction table and extension to strong wind condition >20m/s Conversion table PWI (Precipitalbe water index) to PWA (Precipitable water amount) Correction coefficients on SST dependency No use of internal BT conversion from ver.2 to ver.1 TPW Verification against RAOB (2009.1-5) Collocation criteria: Within 60min. 150km [mm] [mm] ***NEW Num: 1349 Min: -18.836 Max: 19.008 Ave: -0.135 Std: 3.355 *** Current Num: 1344 Min: -18.532 Max: 15.366 Ave: 0.817 Std: 4.071 AMSR-E TPW AMSR-E TPW RAOB TPW RAOB TPW [mm] [mm]

  9. TPW Comparison in Tropics New AMSR-E TPW JAXA AMSR-E L2 TPW 2008.9.15 RSS AMSR-E GRID DATA [mm] Excessive TPW amount in deep convective area (Tropics) Similar to RSS TPW product.

  10. Strong wind condition (>20m/s) TPW Comparison in High latitudes New AMSR-E TPW JAXA AMSR-E L2 TPW 2008.9.15 RSS AMSR-E GRID DATA [mm] Global Analysis: Psea & Surface wind speed 2008.9.15 00UTC [m/s]

  11. TPW retrieval from SSMIS radiance JMA obtains DMSP F-16 and 17 SSMIS data (SDR) from NOAA/NESDIS. Issues on SSMIS data Data quality of lower air sounding channels (LAS) were not good. (i.e. Solar contamination to warm calibration target and antenna emissivity). However, Microwave Imaging channels (ENV) can be used for NWP purpose and atmospheric moisture monitoring. SSMIS frequencies: 19.35 (V,H), 22.235 (V), 37 (V,H), 91.655 (V,H) GHz, zenith angle 53.1 deg. AMSR-E frequencies: 18.7 (V,H), 23.8 (V,H), 36.5(V,H), 89 (V,H) GHz, zenith angle 55.0 deg. AMSR-E TPW algorithm can be applicable for SSMIS TPW retrieval. LUTs for SSMIS were made by using collocated data SSMIS and RAOB.

  12. TPW comparison with SSMIS and SSMI F-16 SSMIS F-17 SSMIS 2008.9.15 F-13 SSMI (from RSS) [mm] Retrieved TPW from F16 and F17 SSMIS seems to be consistent with F-13 SSMI TPW from RSS.

  13. Assimilation experiment of SSMIS TPW in MSM 1st Guess TPW MW-PW, MW-RR, RA SSMIS TPW O-B Analysis time Assimilation time window 09 10 11 12 [mm] [K] 12UTC June 9, 2009 TPW increment WO SSMIS TPW increment W SSMIS Increase of MW data coverage bring much moisture information in oceanic region [mm] [mm]

  14. Assimilation experiment of SSMIS TPW in MSM Operational regional NWP model require much satellite data because rapid updated forecast is essential to provide timely information for disaster prevention SSMI Current data coverage (MW-PW,MW-RR&RA) in MSM DA system 12UTC Jun. 09, 2009 00 03 06 09 AMSR-E 12 15 18 21

  15. Assimilation experiment of SSMIS TPW in MSM Analysis increment of total column water vapor are limited in the satellite data coverage Analysis increment of total column water vapor 12UTC Jun. 09, 2009

  16. Assimilation experiment of SSMIS TPW in MSM Addition of SSMIS TPW can much increase the observation information in MSM DA system DMSP F16&F17 SSMIS TPW data coverage in MSM DA system 12UTC Jun. 09, 2009

  17. Summary and plan • Total Precipitable Water derived from Microwave Imager is crucial data source over ocean in JMA NWP system. • Improvement of MW TPW retrieval algorithm • Update of LUT by using 3-yr RAOB collocated dataset. • Reduced bias in comparison with RAOB, and comparison with RSS TPW product • Available under strong wind condition (over 20m/s) • No use of internal BT conversion from ver.2 to ver.1 • Bias -0.14 [mm] and RMS 3.36 [mm]. Meet GCOM-W/AMSR2 RA requirements • Applicable for SSMIS and other MW Imager data. • Assimilation of SSMIS (F16&F17) TPW retrievals in JMA MSM DA system • Increase the data coverage and fill the data in empty analysis time window • Provided atmospheric water vapor information over the ocean → Hope to see better rainfall forecast • Retrieval of SSMIS TPW is ready. Assimilation experiments are planned to confirm the impacts for the weather forecast.

More Related