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    SA-OBS: A Daily Gridded Surface Temperature and Precipitation Dataset for Southeast Asia

    Source: Journal of Climate:;2017:;volume( 030 ):;issue: 014::page 5151
    Author:
    van den Besselaar, Else J. M.;van der Schrier, Gerard;Cornes, Richard C.;Iqbal, Aris Suwondo;Klein Tank, Albert M. G.
    DOI: 10.1175/JCLI-D-16-0575.1
    Publisher: American Meteorological Society
    Abstract: AbstractThis study introduces a new daily high-resolution land-only observational gridded dataset, called SA-OBS, for precipitation and minimum, mean, and maximum temperature covering Southeast Asia. This dataset improves upon existing observational products in terms of the number of contributing stations, in the use of an interpolation technique appropriate for daily climate observations, and in making estimates of the uncertainty of the gridded data. The dataset is delivered on a 0.25° ? 0.25° and a 0.5° ? 0.5° regular latitude?longitude grid for the period 1981?2014. The dataset aims to provide best estimates of grid square averages rather than point values to enable direct comparisons with regional climate models. Next to the best estimates, daily uncertainties are quantified. The underlying daily station time series are collected in cooperation between meteorological services in the region: the Southeast Asian Climate Assessment and Dataset (SACA&D). Comparisons are made with station observations and other gridded station or satellite-based datasets (APHRODITE, CMORPH, TRMM). The comparisons show that vast differences exist in the average daily precipitation, the number of rainy days, and the average precipitation on a wet day between these datasets. SA-OBS closely resembles the station observations in terms of dry/wet frequency, the timing of precipitation events, and the reproduction of extreme precipitation. New versions of SA-OBS will be released when the station network in SACA&D has grown further.
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      SA-OBS: A Daily Gridded Surface Temperature and Precipitation Dataset for Southeast Asia

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    contributor authorvan den Besselaar, Else J. M.;van der Schrier, Gerard;Cornes, Richard C.;Iqbal, Aris Suwondo;Klein Tank, Albert M. G.
    date accessioned2018-01-03T11:00:56Z
    date available2018-01-03T11:00:56Z
    date copyright4/3/2017 12:00:00 AM
    date issued2017
    identifier otherjcli-d-16-0575.1.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4246060
    description abstractAbstractThis study introduces a new daily high-resolution land-only observational gridded dataset, called SA-OBS, for precipitation and minimum, mean, and maximum temperature covering Southeast Asia. This dataset improves upon existing observational products in terms of the number of contributing stations, in the use of an interpolation technique appropriate for daily climate observations, and in making estimates of the uncertainty of the gridded data. The dataset is delivered on a 0.25° ? 0.25° and a 0.5° ? 0.5° regular latitude?longitude grid for the period 1981?2014. The dataset aims to provide best estimates of grid square averages rather than point values to enable direct comparisons with regional climate models. Next to the best estimates, daily uncertainties are quantified. The underlying daily station time series are collected in cooperation between meteorological services in the region: the Southeast Asian Climate Assessment and Dataset (SACA&D). Comparisons are made with station observations and other gridded station or satellite-based datasets (APHRODITE, CMORPH, TRMM). The comparisons show that vast differences exist in the average daily precipitation, the number of rainy days, and the average precipitation on a wet day between these datasets. SA-OBS closely resembles the station observations in terms of dry/wet frequency, the timing of precipitation events, and the reproduction of extreme precipitation. New versions of SA-OBS will be released when the station network in SACA&D has grown further.
    publisherAmerican Meteorological Society
    titleSA-OBS: A Daily Gridded Surface Temperature and Precipitation Dataset for Southeast Asia
    typeJournal Paper
    journal volume30
    journal issue14
    journal titleJournal of Climate
    identifier doi10.1175/JCLI-D-16-0575.1
    journal fristpage5151
    journal lastpage5165
    treeJournal of Climate:;2017:;volume( 030 ):;issue: 014
    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