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The Evolution of Passive Microwave Precipitation Retrievals - The Impact of A-priori Information

The Evolution of Passive Microwave Precipitation Retrievals - The Impact of A-priori Information. Christian Kummerow Dept. of Atmospheric Science Colorado State University. Global Precipitation Mission. Passive Microwave Signatures. Radiance responds to surface as well as atmosphere

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The Evolution of Passive Microwave Precipitation Retrievals - The Impact of A-priori Information

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  1. The Evolution of Passive Microwave Precipitation Retrievals - The Impact of A-priori Information Christian Kummerow Dept. of Atmospheric Science Colorado State University Global Precipitation Mission

  2. Passive Microwave Signatures • Radiance responds to surface as well as atmosphere • Over oceans, emission from rain column must be distinguished from sfc as well as cloud water • Over land, only ice scattering is easily detectable • Surface rain does is not always well related to integrated water • Conditioned retrievals (e.g. GPROF, GSMAP) can add additional information through a-priori knowledge.

  3. A fuzzy view of a cloud (number) from passive microwave

  4. A fuzzy view of a cloud (number) with a sharper database of possibilities 290 468 127

  5. Radiometer Retrievals trained with CRM data Bayesian Inversion Bayes, T. and R. Prices, 1763: An Essay towards solving a problem in the Doctrine of Chance. By the late Rev. Mr. Bayes, communicated by Mr. Price, in a letter to John Canton, M.A. and F.R.S. Philos. Trans. R. Soc. London, 53, 370-418. Bayes, T. and R. Prices, 1763: An Essay towards solving a problem in the Doctrine of Chance. By the late Rev. Mr. Bayes, communicated by Mr. Price, in a letter to John Canton, M.A. and F.R.S. Philos. Trans. R. Soc. London, 53, 370-418. CRM Database TB observed TB model #1 TB model #2 ~10 km TB model #3 PR/TMI Database of Previously observed Clouds

  6. Radiometer retrievals – CRM based methods • CRMs • TMI • Observations explicit D0 & rice no rain conv rain Tb Retrieval Simulated Tb CRM Output Consistent in Tb? strat

  7. Satellite Rainfall (March 2007) Gprof 2004 TMI AMSR-E

  8. Tropical Rainfall Measuring Mission (TRMM) TRMM Allows Databases to be Constructed from Observations. 5

  9. Radiometer Retrievals trained with PR/TMI data Bayesian Inversion Bayes, T. and R. Prices, 1763: An Essay towards solving a problem in the Doctrine of Chance. By the late Rev. Mr. Bayes, communicated by Mr. Price, in a letter to John Canton, M.A. and F.R.S. Philos. Trans. R. Soc. London, 53, 370-418. Bayes, T. and R. Prices, 1763: An Essay towards solving a problem in the Doctrine of Chance. By the late Rev. Mr. Bayes, communicated by Mr. Price, in a letter to John Canton, M.A. and F.R.S. Philos. Trans. R. Soc. London, 53, 370-418. PR/TMI Database TB observed TB model #1 TB model #2 ~10 km TB model #3 PR/TMI Database of Previously observed Clouds

  10. Retrieval of Precipitation Parameters Ice layer: contributes to scattering at 85 and 37 GHz Melting layer: strongly contributes to emission and radar attenuation Cloud water, water vapor: relatively weak sources of emission and attenuation Rain layer: contributes to emission and radar attenuation

  11. GPROF2010 Dbase ConstructionBased on Column Water Vapor

  12. Radiometer retrievals – PR/TMI based methods • PR/TMI Db • TMI • Observations explicit D0 & rice TPW SST Tb PR/TMI Profiles Retrieval Simulated Tb Consistent in Tb, TPW and SST?

  13. Hurricane Floyd September 13, 1999 GPROF 2008 GPROF 2008 + TRMM radar Parametric GPROF Results (ocean)

  14. Light Rain off the Coast of Africa September 8, 1999 South Africa GPROF 2008 GPROF 2008 + TRMM radar Parametric GPROF Results (ocean)

  15. TMI AMSR-E

  16. The GPM Concept Constellation radiometers are contributed by any agency to produce the frequent sampling required by many applications. • NASA/JAXA contribute Core Satellite Climate Analysis • Precipitation PhysicsGPM Core Satellite carries: - a dual-frequency radar & - a passive microwave imager with • highfrequency capabilities

  17. Radiometer Retrievals trained with DPR/GMI data Bayesian Inversion Bayes, T. and R. Prices, 1763: An Essay towards solving a problem in the Doctrine of Chance. By the late Rev. Mr. Bayes, communicated by Mr. Price, in a letter to John Canton, M.A. and F.R.S. Philos. Trans. R. Soc. London, 53, 370-418. Bayes, T. and R. Prices, 1763: An Essay towards solving a problem in the Doctrine of Chance. By the late Rev. Mr. Bayes, communicated by Mr. Price, in a letter to John Canton, M.A. and F.R.S. Philos. Trans. R. Soc. London, 53, 370-418. DPR/GMI Database TB observed TB model #1 TB model #2 ~10 km TB model #3 PR/TMI Database of Previously observed Clouds

  18. The Retrieval Algorithm Retrievals to search only subset of database with similar ancillary values Input + Ancillary Data Ancillary data will add Surface Temp., Water Vapor, Topography, and Emissivity Class to each profile. e? no yes S1 S0 Retrieval searches profiles of self-similar emissivity classes S1 S2 Retrieval searches a-priori database with same surface properties A channel combination that is insensitive to the surface is compared to a-priori database profiles Retrieval searches profiles of self-similar emissivity classes .

  19. Clustering of emissivities for surface classes (10 surface classes) January July Methodology: - traditional k-meansclustering - use of NSIDC data for snow - use of our global wetlanddataset Standing water Snow & ice decreasing vegetation

  20. Ancillary Data - Topography Elevation  1 km global elevation from GLOBE, Sampled to 1/10 of a degree (12 km). Includes standard deviation of elevation within the sampled 10X10 footprint.

  21. Radiometer retrievals – PR/TMI based methods • DPR/GMI Db • TMI • Observations explicit D0 & rice TPW SST Tb PR/TMI Profiles Retrieval Simulated Tb Consistent in Tb, TPW and Tsfc eclass, Topo?

  22. AMSR-E Tbs with AMSR-E/CloudSat Database S1 Retrieval January 7th, 2009 SNODAS snow extent 8Z 10Z 8Z 10Z 10Z 8Z GPM Radiometer Algorithm Meeting U. Maryland, July 16,17, 2012

  23. Need to find appropriate ancillary data

  24. GPM will likely resolve differences in climate sensitivity between Radar and Radiometer. We continue to look for robust ancillary information that describes precipitating clouds in a self similar manner – argue that radiometers by themselves, do not have enough information content to distinguish small changes in cloud properties from changes in surface precipitation. Physical retrieval schemes allow for validation of model processes – not simply model output. Conclusion (2012)

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