Recent activities on AMSR-E data utilization in NWP

Recent activities on AMSR-E data utilization in NWP at JMA Masahiro Kazumori, Koichi Yoshimoto, Takumu Egawa Numerical Prediction Division Japan Meteorological Agency 2 -3 June, 2010 AMSR-E Science Team Meeting, Huntsville, AL, U. S. A.

Outline Status of JMA NWP models and Microwave imager data utilization Verification of AMSR-E TPW retrieval algorithm with global GPS TPW data Application to SSMIS TPW retrieval and the assimilation experiment in JMA NWP Expectations for Microwave imager data Observational local time Data latency Summary

JMA NWP models Purposes Forecast domain Grid size and/or number of grids Vertical levels / Top Forecast hours (Initial time) Analysis Global Model (GSM) Short- and medium-range forecast Globe Meso Scale Model (MSM) Very-short-range forecast Japan and its surrounding areas 0. 1875 deg. (TL 959) 5 km / 721 x 577 60 / 0. 1 h. Pa 84 hours (00, 06, 18 UTC) 216 hours (12 UTC) 4 D-Var 50 / 21, 800 m 15 hours (00, 06, 12, 18 UTC) 33 hours (03, 09, 15, 21 UTC) 4 D-Var

MW Imager data utilization in JMA For Global Model: Radiance assimilation Brightness Temperature in clear sky condition Data thinning : 200 km grid box QC : cloud screening and bias correction Colored point data are actually assimilated. For Meso scale Model: Retrieval Assimilation Total Precipitable Water(TPW) and Rain Rate (RR)

Recent update in MSM Ground based GPS TPW data in Japan was introduced in operational JMA MSM DA system in Oct. 2009. The GPS data provide accurate and periodic TPW information over land. Improvements of rain prediction were confirmed in heavy rain cases. Atmospheric moisture information is essential to produce better rain forecast. Also global GPW TPW data set are available in JMA for verifications of NWP model’s TPW and satellite TPW products. Analyzed precipitation GPS data are delivered from Geospatial Information Authority of Japan (GSI) and converted to TPW products in JMA. With GPS Without GPS Three-hourly accumulated precipitation of 3 -hour forecasts from 20 Jul. 2009 at an initial time of 21 UTC. From the left, analyzed precipitation, the forecast of Test (with GPS TPW) and that of Control (without GPS TPW).

Verification of AMSR-E TPW products with global GPS TPW data Locations of collocated GPS Data (35 sites) ZTD ：Zenith Tropospheric Delay ZHD : Zenith Hydrostatic Delay ZWD : Zenith Wet Delay AMSR-E and GPS collocation criteria: GPS altitude <= 200 m, GPS analysis Spatial diff. <= 20 km, ・GPS satellite ephemeris : final ephemeris of International Time diff. <= 10 min. Global Navigation Satellite System Service (IGS). Period: 20 Jun. – 20 Aug. 2009 ・GPS data (RINEX) : IGS station ・Software : GIPSY/OASIS-II

Verification of AMSR-E TPW products with global GPS TPW data Scatter diagram of TPW GPS vs. AMSR-E NEW The National Snow and Ice JAXA-L 2 Data Center (NSIDC)

Verification of AMSR-E TPW products by global GPS TPW data set TPW’s time sequences for NEW, JAXA-L 2, and NSIDC products CHICHIJIMA Chatham Island

A case study: Assimilation of SSMIS TPW & RR in MSM Heavy rain case in Japan July 19 – 26, 2009 Time sequence of observed hourly rain fall in Yamaguchi prefecture Hourly Rainfall (left axis) Total Rainfall (right axis) The average year value for July’s one month rainfall 00 UTC Jul. 21, 2009 MTSAT IR image 24 hr observed rainfall

Data coverage of Microwave Imager data in JMA MSM SSMIS TPW and RR assimilation period : July 19 to 26, 2009 MSM analyses were executed in every 3 hour (00, 03, 06, 09, 12, 15, 18 and 21 UTC) 33 hours forecasts were produced from 03, 09, 15 and 21 UTC initial. Cntl (W/O SSMIS) 00 03 06 09 12 15 18 21 Test (With SSMIS) 00 03 SSMIS data is available in these analysis time Red : F 13 SSMI Blue : TRMM TMI Light Blue : Aqua AMSR-E Green : F 16 SSMIS Purple : F 17 SSMIS

Impact on moisture analysis in July 20 Analyzed TPW field in Test (with SSMIS) 03 UTC 09 UTC 15 UTC 21 UTC TPW Analysis difference (Test-Cntl) Generally, assimilation of SSMIS intensify moisture flow in the analysis.

Jul. 20 15 UTC INITIAL FT=0 TEST TPW DIFF (TEST-CNTL) 12

FT=1 [hour] TEST TPW DIFF (TEST-CNTL) 13

FT=2 TEST TPW DIFF (TEST-CNTL) 14

FT=3 TEST TPW DIFF (TEST-CNTL) 15

FT=4 TEST TPW DIFF (TEST-CNTL) 16

FT=5 TEST TPW 1 -4 March 2010 TPW DIFF (TEST-CNTL) 17

FT=6 TEST TPW DIFF (TEST-CNTL) 18

FT=7 TEST TPW DIFF (TEST-CNTL) 19

FT=8 TEST TPW DIFF (TEST-CNTL) 20

FT=9 TEST TPW DIFF (TEST-CNTL) 21

FT=10 TEST TPW DIFF (TEST-CNTL) 22

FT=11 TEST TPW DIFF (TEST-CNTL) 23

FT=12 TEST TPW DIFF (TEST-CNTL) 24

Impact on Rain Forecast Valid Time: Jul. 21 12 JST TEST (with SSMIS) Radar observation 3 hr rain CNTL(w/o SSMIS) FT=12 Strong rain band appeared, but, the crossing time of the rain band was not improved. TEST TPW TEST-CNTL TPW DIFF FT=12 [mm] Increased TPW in moist area, decreased in dry area. SSMIS intensified the moisture flow in the forecast

Observational Local Time Light Blue : Aqua/AMSR-E Purple : DMSP F-16/SSMIS Green : DMSP F-17/SSMIS Orange : Coriolis/Wind. Sat 00 For the purpose of operational use of satellite microwave imager data in NWP, observational local time is a key element. NWP centers use 6 hrs assimilation time window. Continuity of MW measurements in A-train is indispensable. 06 18 12 13: 30 Dark black points indicate Wind. Sat data in 6 -hrs time window

Data Latency Timely data delivery is also important for the use of satellite data in operational NWP. Especially, regional analysis demand strict cut off time for data receiving. MSM requires 50 min cut off time after the analysis time for every analysis (8 time/day). Direct receiving in the frame work of WMO RARS and EARS are suitable for the regional data use for ATOVS. Data latency for ATOVS (MSC) Data latency for AMSR-E (JAXA) Data latency for MTSAT Data latency for AMSR-E (Global)

Summary TPW data from MW-Imager play important role for accurate rain forecasts in MSM. TPW retrieval algorithm was verified with ground based GPS TPW data. Improvement was found compared with current JAXA L 2 product, however, there is room for further improvement. NSIDC products showed better accuracy in GPS TPW verification. The algorithm was applied for F-16 and F-17 SSMIS. The retrieved TPW and RR were assimilated in JMA MSM for a heavy rain case in Japan. Assimilation of new SSMIS TPW data produced strong rain band forecast, but the forecasted rain band location was not improved. Data coverage is a key issue for satellite data utilization in operational NWP. Large coverage in each analysis is expected with timely data delivery. AMSR-E observation in afternoon orbit (A-train) is indispensable.

Backup slides

Comparison between RAOB and GPS (Spatial diff. <30 km, altitude diff. < 200 m)

GPS Remote Sensing GPS satellite Vapor Pseudo Range Zenith Tropospheric Delay = Zenith Hydrostatic Delay ＋ Zenith Wet Delay Procedure GPS observation data (RINEX) Receiver ZTD GPS software（ GIPSY） GPS ephemeris　　 Conversion Surface Pressure, Temperature TPW

Other data’s coverage in MSM

Theoretical basis of the algorithm (1. 1) (1. 2) (1. 3) (1. 4) Microwave Brightness temperature Eq. Ta is defined as the average of upward Tu and downward Td Water vapor Ta is equal to cloud liquid water Ta : Observed brightness temperature : Mean emission temperature : Atmospheric Transmittance : Ocean surface emissivity Vertical mean temperature of atmosphere and ocean surface system Step 1 Determination of by pre-defined LUT as a function of frequency, incidence angle, SST and SSW Step 2 Initial atmospheric transmittance is set as exp(-0. 2) Step 3 Determination of Step 4 Calculation of mean emission temperature by using Eq. (1 -4) Step 5 Calculation of Transmittance (V pol. & H pol. ) by using Eq. (1 -3) Step 6 Calculation of new transmittance by pre-defined LUT of and T 850 based on RAOB Iteration calculation of Step 3 – 6 to obtain optimized Transmittance

Retrieval of TPW and CLW Theoretical calculation TPW From Eq. (1. 2) TPW can be derived by absorption coefficients of water vapor kv and cloud liquid water kl by using two different frequency. However, it is not able to calculate kv and kl because these depend on vertical profile of temperature, water vapor and liquid water. a function of SST Determined to be maximize the correlation between TPW index and RAOB match-up TPW CLW A function decreased with TPW A constant Theoretically estimated

Updated 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 : T 850, Transmittance and Mean atmospheric temperature table Wind speed correction table and extended to strong wind condition beyond 20 m/s Conversion table PWI (Precipitable water index) to TPW Correction coefficients on SST , SSW dependency of emissivity No use of internal Tb conversion from ver. 2 to ver. 1 (JAXA L 1 B Tb version) [mm] Collocation criteria: Within 60 min. 150 km AMSR-E TPW *** Current Num: 1344 Min: -18. 532 Max: 15. 366 Ave: 0. 817 Std: 4. 071 AMSR-E TPW ***NEW Num: 1349 Min: -18. 836 Max: 19. 008 Ave: -0. 135 Std: 3. 355 [mm] TPW Verification against RAOB (2009. 1 -5) RAOB TPW [mm]

V 003 vs GPS_PWV （2009年 6月20日～ 8月20日） (mm) Ver. 003

Optimized by 3 years RAOB TPW data 2007 - 2009 (mm) Ver. 004

Optimized by 3 months GPS TPW data Jun. 20 – Aug. 20, 2009 (mm) Ver. 005 (preliminary)