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    Reprocessed, Bias-Corrected CMORPH Global High-Resolution Precipitation Estimates from 1998

    Source: Journal of Hydrometeorology:;2017:;Volume( 018 ):;issue: 006::page 1617
    Author:
    Xie, Pingping
    ,
    Joyce, Robert
    ,
    Wu, Shaorong
    ,
    Yoo, Soo-Hyun
    ,
    Yarosh, Yelena
    ,
    Sun, Fengying
    ,
    Lin, Roger
    DOI: 10.1175/JHM-D-16-0168.1
    Publisher: 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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      Reprocessed, Bias-Corrected CMORPH Global High-Resolution Precipitation Estimates from 1998

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    contributor authorXie, Pingping
    contributor authorJoyce, Robert
    contributor authorWu, Shaorong
    contributor authorYoo, Soo-Hyun
    contributor authorYarosh, Yelena
    contributor authorSun, Fengying
    contributor authorLin, Roger
    date accessioned2017-06-09T17:17:19Z
    date available2017-06-09T17:17:19Z
    date issued2017
    identifier issn1525-755X
    identifier otherams-82457.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4225573
    description abstracthe 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.
    publisherAmerican Meteorological Society
    titleReprocessed, Bias-Corrected CMORPH Global High-Resolution Precipitation Estimates from 1998
    typeJournal Paper
    journal volume018
    journal issue006
    journal titleJournal of Hydrometeorology
    identifier doi10.1175/JHM-D-16-0168.1
    journal fristpage1617
    journal lastpage1641
    treeJournal of Hydrometeorology:;2017:;Volume( 018 ):;issue: 006
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian