92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Wednesday, 25 January 2012: 11:15 AM
Recent Advances in the GPCP Global Precipitation Record
Room 257 (New Orleans Convention Center )
David T. Bolvin, SSAI and NASA/GSFC, Greenbelt, MD; and R. F. Adler, G. J. Huffman, L. S. Chiu, E. J. Nelkin, U. Schneider, and D. A. Vila

The Global Precipitation Climatology Project (GPCP) is charged with developing global long-term records of precipitation for the international community on behalf of the World Meteorological Organization/World Climate Research Programme/Global Energy and Water Experiment (WMO/WCRP/GEWEX). After an extended period of stable input data and algorithms the GPCP has entered a period in which a variety of upgrades and transitions are needed to enhance and continue extending the data record. In late July 2011 the GPCP monthly Satellite-Gauge dataset was reprocessed and restarted as Version 2.2, followed thereafter by the One-Degree Daily (1DD) dataset as Version 1.2.

Most notably, the failure in September 2009 of the SSM/I sensor on the DMSP F13 satellite deprived the GPCP of its long-time source of precipitation estimates that were used as the calibration standard. Although the DMSP F17 SSMIS sensor is the clear choice as the new standard to maintain record consistency, calibration issues are only now being resolved. We will describe the bridge algorithm we developed based on the DMSP F17 SSMIS sensor. In addition, new, consistently processed versions of the ocean microwave algorithm (which is relatively unaffected by the F17 issues), land microwave algorithm, and surface gauge analysis were incorporated, and these will be summarized. The net result is not only longer data records, but also records that are more homogeneous, bringing them into closer conformance with the concept of Climate Data Records.

The paper will close with a brief review of the performance of the new datasets compared to the previous versions. In general, there is strong consistency between the monthly Versions 2.1 and 2.2, with most differences occurring in a few well-identified periods of record. The change in 1DD versions shows somewhat larger differences because the revised GPROF algorithm used to estimate fractional coverage by precipitation during the month has noticeably higher coverage in many locations than the legacy GPROF version used in the previous 1DD dataset.

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