8.6 A multi-sensor merged analysis of high-resolution global precipitation analysis

Wednesday, 26 January 2011: 5:15 PM
611 (Washington State Convention Center)
Pingping Xie, NOAA/NWS/NCEP, Camp Springs, MD; and S. H. Yoo, R. J. Joyce, and Y. S. Yarosh

As part of the CPC Unified Precipitation Products Project, a suite of hourly and daily precipitation analyses have been constructed on a 0.25olat/lon grid over the globe for a 13-year period from 1998 to the present, by combining information derived from CMORPH high-resolution satellite estimates, CPC unified daily gauge analysis, and the long-term low-resolution pentad GPCP product. Special attention has been paid in the development of this products suite to ensure quantitative consistency of this high-resolution but relatively short precipitation analysis with long-term climate record. To this end, the original CMORPH satellite estimates are adjusted against two sets of widely used long-term data sets, the CPC unified gauge analysis over land and the pentad GPCP over ocean, respectively.

First, bias correction is performed for the CMORPH satellite estimates. This is done by matching the PDF of the CMORPH estimates with the daily gauge analysis over land and with the pentad GPCP analysis over ocean. The correction coefficients are applied to remove the bias in the CMORPH at its original resolution of 8Km/30-min. The bias corrected CMORPH is then accumulated to a time/space resolution of hourly/0.25olat/lon. Over the global land areas, the bias corrected CMORPH is further accumulated to daily time scale and combined with the gauge analysis for improved quality. This is done through the optimal interpolation (OI) technique in which the satellite estimates are used as the first guess while the gauge data are utilized to refine the first guess over areas with station observations. Examinations of this new gauge-satellite merged precipitation analysis showed substantial improvements against the input gauge analysis, the CMORPH satellite estimates, and the previous CPC merged analyses. Details of the data sets construction and their applications will be presented at the workshop.

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