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Development, Implementation, Validation, and Analysis of Quasi-Global Combined-Sensor Precipitation Estimates at Fine Scales for TRMM and GPM

Principal Investigator

George J Huffman
NASA/Goddard Space Flight Center
Code 613.1
Greenbelt, MD 20771

E-mail: george.j.huffman.1@gsfc.nasa.gov
Phone: 301-614-6308
Fax: 301-614-5492

Abstract

We propose to continue development of quasi-global, multi-satellite precipitation analyses at fine time/space scales for TRMM and GPM, and to analyze such data sets for improvement in understanding of weather systems and their relation to inter-annual and longer variations in precipitation. The key product concept is the TRMM Multi-satellite Precipitation Analysis (TMPA) that currently uses TRMM data to calibrate or adjust the rain estimates from other satellites (primarily passive microwave) and then combines those calibrated estimates into an analysis with 3-hour resolution. In the formal TRMM data system this TMPA product is known as 3B42, and there is a companion monthly 3B43 product. In the current funding cycle more than eight years of the TMPA standard product have been produced in Version 6 of TRMM processing, and it has become the most requested TRMM product in the Goddard DAAC. A real-time version of this product is computed with similar procedures and also publicly available. The PI and the research team of which he is a part in the GSFC Laboratory for Atmospheres have had comprehensive responsibility for all of these multi-satellite standard products since their inception over a decade ago. The intended outcome of this work is improvement in the combined precipitation estimates around the globe, coupled with improved scientific characterization of the global precipitation. Such advances will most directly improve estimates and understanding of the precipitation flux in the global water cycle (Science Outcome 3A.4). They will also improve both the input to predictions of weather, including extreme weather, and the quasi-global characterization of precipitation for validation of weather and extreme weather predictions (Science Outcome 3A.2). Finally, the advances are instituted in a suite of nearly complete fine-scale fields, computed first in real time and then upgraded when additional data become available (Science Outcome 3A.7).





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