Reprocessed, Bias-Corrected CMORPH Global High-Resolution Precipitation Estimates from 1998Source: Journal of Hydrometeorology:;2017:;Volume( 018 ):;issue: 006::page 1617Author:Xie, Pingping
,
Joyce, Robert
,
Wu, Shaorong
,
Yoo, Soo-Hyun
,
Yarosh, Yelena
,
Sun, Fengying
,
Lin, Roger
DOI: 10.1175/JHM-D-16-0168.1Publisher: American Meteorological Society
Abstract: he Climate Prediction Center (CPC) Morphing technique (CMORPH) satellite precipitation estimates are reprocessed and bias-corrected on an 8kmx8km grid over the globe (60°S-60°N) and in a 30-minute temporal resolution for an 18-year period from January 1998 to the present to form a climate data record (CDR) of high-resolution global precipitation analysis. First, the purely satellite based CMORPH precipitation estimates (raw CMORPH) are reprocessed. The integration algorithm is fixed and the input Level 2 passive microwave (PMW) retrievals of instantaneous precipitation rates are from identical versions throughout the entire data period. Bias correction is then performed for the raw CMORPH through probability density function (PDF) matching against the CPC daily gauge analysis over land and through adjustment against the Global Precipitation Climatology Program (GPCP) pentad merged analysis of precipitation over ocean. The reprocessed, bias-corrected CMORPH exhibits improved performance in representing the magnitude, spatial distribution patterns and temporal variations of precipitation over the global domain from 60°S to 60°N. Bias in the CMORPH satellite precipitation estimates is almost completely removed over land during warm seasons (May ? September), while during cold seasons (October to April) CMORPH tend to under-estimate the precipitation due to the less-than-desirable performance of the current generation PMW retrievals in detecting and quantifying snowfall and cold season rainfall. An inter-comparison study indicated that the reprocessed, bias-corrected CMORPH exhibits consistently superior performance than the widely used TRMM 3B42 (TMPA) in representing both daily and 3-hourly precipitation over CONUS and other global regions.
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contributor author | Xie, Pingping | |
contributor author | Joyce, Robert | |
contributor author | Wu, Shaorong | |
contributor author | Yoo, Soo-Hyun | |
contributor author | Yarosh, Yelena | |
contributor author | Sun, Fengying | |
contributor author | Lin, Roger | |
date accessioned | 2017-06-09T17:17:19Z | |
date available | 2017-06-09T17:17:19Z | |
date issued | 2017 | |
identifier issn | 1525-755X | |
identifier other | ams-82457.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4225573 | |
description abstract | he Climate Prediction Center (CPC) Morphing technique (CMORPH) satellite precipitation estimates are reprocessed and bias-corrected on an 8kmx8km grid over the globe (60°S-60°N) and in a 30-minute temporal resolution for an 18-year period from January 1998 to the present to form a climate data record (CDR) of high-resolution global precipitation analysis. First, the purely satellite based CMORPH precipitation estimates (raw CMORPH) are reprocessed. The integration algorithm is fixed and the input Level 2 passive microwave (PMW) retrievals of instantaneous precipitation rates are from identical versions throughout the entire data period. Bias correction is then performed for the raw CMORPH through probability density function (PDF) matching against the CPC daily gauge analysis over land and through adjustment against the Global Precipitation Climatology Program (GPCP) pentad merged analysis of precipitation over ocean. The reprocessed, bias-corrected CMORPH exhibits improved performance in representing the magnitude, spatial distribution patterns and temporal variations of precipitation over the global domain from 60°S to 60°N. Bias in the CMORPH satellite precipitation estimates is almost completely removed over land during warm seasons (May ? September), while during cold seasons (October to April) CMORPH tend to under-estimate the precipitation due to the less-than-desirable performance of the current generation PMW retrievals in detecting and quantifying snowfall and cold season rainfall. An inter-comparison study indicated that the reprocessed, bias-corrected CMORPH exhibits consistently superior performance than the widely used TRMM 3B42 (TMPA) in representing both daily and 3-hourly precipitation over CONUS and other global regions. | |
publisher | American Meteorological Society | |
title | Reprocessed, Bias-Corrected CMORPH Global High-Resolution Precipitation Estimates from 1998 | |
type | Journal Paper | |
journal volume | 018 | |
journal issue | 006 | |
journal title | Journal of Hydrometeorology | |
identifier doi | 10.1175/JHM-D-16-0168.1 | |
journal fristpage | 1617 | |
journal lastpage | 1641 | |
tree | Journal of Hydrometeorology:;2017:;Volume( 018 ):;issue: 006 | |
contenttype | Fulltext |