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    Derivation of New Daily Rainfall Values from TAO 1-Min Rain Gauge Data

    Source: Journal of Atmospheric and Oceanic Technology:;2022:;volume( 039 ):;issue: 011::page 1729
    Author:
    Werner E. Cook
    ,
    J. Scott Greene
    DOI: 10.1175/JTECH-D-22-0011.1
    Publisher: American Meteorological Society
    Abstract: Daily rainfall accumulation estimates have been derived from 1-min volume data collected via self-syphon rain gauges deployed in the Tropical Atmosphere–Ocean (TAO) array of oceanographic buoys. The underlying high-resolution volume data were obtained directly from the Global Tropical Moored Buoy Array (GTMBA) Project Office of NOAA/Pacific Marine Environmental Laboratory. The derived accumulations have been incorporated into the Pacific Rainfall (PACRAIN) database as estimated daily values to augment existing sea level oceanic rainfall records gathered using traditional rain gauges. They have also been included in the PACRAIN historical, monthly gridded rainfall product. The methodology presented, which employs differencing of least squares–regressed sensor levels about 0000 UTC and rain gauge syphon events, is shown to offer improved error characteristics over the methodology used to compute previously published GTMBA rain rates. In particular, the PACRAIN method yields larger coefficients of determination and smaller standard errors than the duplicated GTMBA method when applied to synthetic rainfall data with noise magnitude and decorrelation times encompassing those observed in the real 1-min data. These results are shown to be consistent with mathematical expectations. Sources of instrument and catchment errors, as well as evaporation, are discussed in the context of their potential effects on accumulation estimates for periods of a day or longer.
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      Derivation of New Daily Rainfall Values from TAO 1-Min Rain Gauge Data

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4289679
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    contributor authorWerner E. Cook
    contributor authorJ. Scott Greene
    date accessioned2023-04-12T18:26:40Z
    date available2023-04-12T18:26:40Z
    date copyright2022/11/01
    date issued2022
    identifier otherJTECH-D-22-0011.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4289679
    description abstractDaily rainfall accumulation estimates have been derived from 1-min volume data collected via self-syphon rain gauges deployed in the Tropical Atmosphere–Ocean (TAO) array of oceanographic buoys. The underlying high-resolution volume data were obtained directly from the Global Tropical Moored Buoy Array (GTMBA) Project Office of NOAA/Pacific Marine Environmental Laboratory. The derived accumulations have been incorporated into the Pacific Rainfall (PACRAIN) database as estimated daily values to augment existing sea level oceanic rainfall records gathered using traditional rain gauges. They have also been included in the PACRAIN historical, monthly gridded rainfall product. The methodology presented, which employs differencing of least squares–regressed sensor levels about 0000 UTC and rain gauge syphon events, is shown to offer improved error characteristics over the methodology used to compute previously published GTMBA rain rates. In particular, the PACRAIN method yields larger coefficients of determination and smaller standard errors than the duplicated GTMBA method when applied to synthetic rainfall data with noise magnitude and decorrelation times encompassing those observed in the real 1-min data. These results are shown to be consistent with mathematical expectations. Sources of instrument and catchment errors, as well as evaporation, are discussed in the context of their potential effects on accumulation estimates for periods of a day or longer.
    publisherAmerican Meteorological Society
    titleDerivation of New Daily Rainfall Values from TAO 1-Min Rain Gauge Data
    typeJournal Paper
    journal volume39
    journal issue11
    journal titleJournal of Atmospheric and Oceanic Technology
    identifier doi10.1175/JTECH-D-22-0011.1
    journal fristpage1729
    journal lastpage1749
    page1729–1749
    treeJournal of Atmospheric and Oceanic Technology:;2022:;volume( 039 ):;issue: 011
    contenttypeFulltext
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