NDLI: Verification of Cloud Dynamics and Radiation Database (CDRD) passive microwave precipitation retrieval algorithm using TRMM satellite radar and radiometer measurements over Southern Mediterranean Basin

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Verification of Cloud Dynamics and Radiation Database (CDRD) passive microwave precipitation retrieval algorithm using TRMM satellite radar and radiometer measurements over Southern Mediterranean Basin

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2006 IEEE MicroRad

Verification of Cloud Dynamics and Radiation Database (CDRD) passive microwave precipitation retrieval algorithm using TRMM satellite radar and radiometer measurements over Southern Mediterranean Basin

Content Provider	IEEE Xplore Digital Library
Author	Casella, D. Dietrich, S. Formenton, M. Mugnai, A. Panegrossi, G. Sano, P. Smith, E.A. Tripoli, G.J.
Copyright Year	2012
Description	Author affiliation: ISAC-CNR Rome, ITALY (Casella, D.; Dietrich, S.; Formenton, M.; Mugnai, A.; Panegrossi, G.; Sano, P.) \|\| Dept. of Atmospheric and Oceanic Sciences (AOS), University of Wisconsin, Madison, USA (Tripoli, G.J.) \|\| Center for Research on the Changing Earth System (CRCES), Tallahassee, FL, USA (Smith, E.A.)
Abstract	A verification study is conducted for the Cloud Dynamics and Radiation Database (CDRD) rainfall algorithm over the southern Mediterranean Basin (25–36° N / 25° W–45° E), based on TRMM Microwave Imager (TMI) passive microwave (PMW) brightness temperature (TB) measurements. The CDRD's required synthetic database is generated from a high resolution, nonhydrostatic cloud resolving model equipped with a precision RTE model. This dual modeling system is used to simulate numerous and precipitating storms over Europe and across the Mediterranean Basin as the database's foundation. Extracted from the simulations for the database are the a priori knowledge variables involving many thousands of synthetic precipitating microphysical-meteorological profiles and their concomitant synthetic multi-frequency PMW TBs. This information provides the probability framework for the CDRD algorithm's Bayesian inversion process and thus the means to relate measured satellite TBs to the most probable rainfall solutions. As the newest algorithm feature, the CDRD scheme makes use of meteorological parameters (tags) of observed precipitation systems, obtained from global NWP model synthesized initialization data, for both precipitation regime recognition and Bayesian retrieval constraints. These two steps effectively reduce non-uniqueness problems in obtaining retrieval solutions. Comparison of TMI-based CDRD retrievals to coincident TRMM Precipitation Radar (PR) retrievals, used as ground truth, provides the means to assess the algorithm's performance and the twofold use of meteorological tag information for control and constraint. PR-retrieved cloud property parameters (e.g., freezing level) are also compared to NWP model tags to further verify algorithm design performance. The verification procedure utilizes a full year (2010) of TMI and PR measurements, indicating CDRD over-ocean and over-land results are within 0.10 and 0.17 mm hr-1 of the PR means, with accompanying 1.24 and 2.94 mm hr-1 rms errors. The CDRD algorithm is also compared to the TRMM TMI facility algorithm (2al2-v7), exhibiting slight improvement over water (in correlation coefficient) and significantly improvement over land. Error statistics indicate CDRD vis-a-vis 2al2 over-land improvements of 78% and 14% in regards to mean error and rms error, respectively.
Starting Page	1
Ending Page	4
File Size	969970
Page Count	4
File Format	PDF
ISBN	9781467314688
e-ISBN	9781467314701
DOI	10.1109/MicroRad.2012.6185243
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-05
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bayesian Passive Microwave Precipitation Retrieval Sea measurements Meteorological Constraints Precipitation Regime Recognition Argon Reliability Object recognition Spatial resolution CDRD Rainfall Algorithm Verification TRMM TMI and PR Precipitation Retrievals
Content Type	Text
Resource Type	Article

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