for the Global Precipitation Mission

Transcription

1 A Physically based Rainfall Rate Algorithm for the Global Precipitation Mission Kevin Garrett 1, Leslie Moy 1, Flavio Iturbide Sanchez 1, and Sid Ahmed Boukabara 2 5 th IPWG Workshop Hamburg, Germany October 12, I. M. Systems Group 2. NOAA/NESDIS/STAR, JCSDA

2 Agenda Overview of the Microwave Integrated Retrieval System (MiRS) The MiRS Testbed MiRS for TRMM and GPM Next Steps and Summary

3 Overview NOAA/NESDIS/STAR S/S has developed e a flexible bephysical ysca algorithm: the Microwave Integrated Retrieval System (MiRS) Can be applied to any microwave sounder/imager 1DVAR approach using CRTM as forward and jacobian operators Retrieves sounding and surface parameters simultaneously, including hydrometeor profiles and rainfall rate Applicable over all surfaces and in all weather conditions Run operationally at NOAA OSDPD (and integrated at NDE for NPP/JPSS future processing) MiRS is currently being extended to support GPM

4 MiRS in Context DMSP SSMIS F16/F18 Metop A POES N18/N19 MiRS is applied to a number of microwave sensors, each time gaining robustness and improving validation for Future New Sensors The exact same executable, forward operator, covariance matrix used for all sensors Modular design Cumulative validation and consolidation of MiRS AQUA AMSR E NPP/NPOESS ATMS TRMM/GPM/ M T TMI, GMI proxy, SAPHIR/MADRAS : Applied Operationally : Applied occasionally : Tested in Simulation

5 Algorithm Description 1 T 1 1 m T Satellite Tbs VIPP 1 m J(X) Calibration X X0 B X X0 Y Y(X) E Y Y(X) 2 2 Preprocessing NEDT Resolution Bias Correction Preclassifier ΔX 1DVAR Corrected Tbs Ym Simulated Tbs Y Ym Y fit within NEDT? n 1 Solution YES NO Update X BK T n K nbk T n Temp. Profile 1 Humidity Profile n E Liq. Amount Prof Y m Y(X n) K TPW n ΔX n CLW Ice Amount Prof IWP Rain Amount Prof RWP Emissivity Spectrum SIC/SWE Skin Temperature n Rainfall Rate RR = c 0 + c 1 RWP+c 2 IWP+c 3 CLW CRTM State Vector X First Guess /Background Rainfall rate based on relationship to integrated hydrometeor values Coefficients derived from MM5 simulations Daily GlobalPrecipitation Estimate (PE) computed from MiRS POES, Metop and DMSP instantaneous RR

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7 Independent Validation through IPWG Provide MiRS PE over CONUS, S.A. and Australia Independent assessment versus radars/gauges Comparison to other precipitation algorithms Images courtesy of John Janowiak, UMD; Daniel Vila, CPTEC; and Elizabeth Ebert, Australian Bureau of Meteorology

8 Independent Validation through IPWG Monitor a running time series of statistics relative to rain gauges Intercomparison with other p PE algorithms and radar

9 MiRS Testbed Comparison to 24 hr. PE to CPC Rain Gauge Analysis (top) and time series of PoD and Correlation from May 2009 Aug Time series comparison of MiRS RR to NCEP Stage IV PoD and Correlation, Sept 2009 Sept

10 MiRS Testbed Rainfall Climatologies Hydrometeor Profiles/Vertical Cross Sections Monthly Averaged MiRS NOAA 18 Rainfall Rate for 2009, 1 grid MiRS Hydrometeor Profiles Monthly Averaged MSPPS NOAA 18 Rainfall Rate for , 1 grid TRMM 2A12 Hydrometeor Profiles

11 MiRS for TRMM/GPM MiRS will be extended to the Global Precipitation Mission i Microwave Imager GMI is similar to TRMM Microwave Imager with additional high frequency channels (166 and 183 GHz) MiRS has been extended to TMI and GMI simulated data MiRS will also be extended to Megha Tropiques es SAPHIR/MADRAS

12 MiRS for TRMM/GPM Example of retrieved rainfall rate from MiRS on TMI data at ~5 km resolution (left) compared to TRMM 2A12 (right) (ih)for

13 MiRS for GPM Next Steps Enhanced hydrometeor profile and rainfallrate rate retrievals Profiles constrained by latitude and season Rainfall rate relationships to integrated hydrometeors by latitude and season Mid latitude Profiles Tropical Profiles Rain Ice Ice WRF Model Simulation Rain WRF Model Simulation

14 Summary MiRS is an operational algorithm at NOAA/NESDIS and provides important hydrological information MiRS will be applied to GMI observations in the future Current enhancements to the algorithm expected to improve performances of hydrometeor retrievals for all sensors

15 More Information Publications S. A. Boukabara, K. Garrett, and W. Chen, Global Coverage of Total Precipitable Water using a Microwave Variational Algorithm, IEEE TGARS, vol. 48, Sept F. Iturbide Sanchez, S. A. Boukabara, R. Chen, K. Garrett, C. Grassotti, W. Chen, and F. Weng, Assessment of a Variational Inversion System for Rainfall Rate over Land and Water Surfaces, Submitted IEEE TGARS, July S. A. Boukabara et al. MiRS: An All Weather 1DVAR Satellite Data Assimilation and Retrieval System, Submitted IEEE TGARS, May Website p//