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      <source-app name="Horizon">Horizon</source-app>
      <rec-number>1</rec-number>
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      <ref-type name="Journal Article">17</ref-type>
      <work-type>ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES</work-type>
      <contributors>
        <authors>
          <author>
            <style face="bold" font="default" size="100%">Satgé, Frédéric</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Hussain, Y.</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Molina-Carpio, J.</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Pillco, R.</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Laugner, C.</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Akhter, G.</style>
          </author>
          <author>
            <style face="bold" font="default" size="100%">Bonnet, Marie-Paule</style>
          </author>
        </authors>
      </contributors>
      <titles>
        <title>Reliability of SM2RAIN precipitation datasets in comparison to gauge observations and hydrological modelling over arid regions</title>
        <secondary-title>International Journal of Climatology</secondary-title>
      </titles>
      <pages>E517-E536</pages>
      <keywords>
        <keyword>arid region</keyword>
        <keyword>assessment</keyword>
        <keyword>gauges</keyword>
        <keyword>hydrological modelling</keyword>
        <keyword>satellite</keyword>
        <keyword>precipitation</keyword>
        <keyword>SM2RAIN</keyword>
        <keyword>ZONE ARIDE</keyword>
        <keyword>BOLIVIE</keyword>
        <keyword>PEROU</keyword>
        <keyword>PAKISTAN</keyword>
      </keywords>
      <dates>
        <year>2021</year>
      </dates>
      <call-num>fdi:010079415</call-num>
      <language>ENG</language>
      <periodical>
        <full-title>International Journal of Climatology</full-title>
      </periodical>
      <isbn>0899-8418</isbn>
      <accession-num>ISI:000550978700001</accession-num>
      <number>suppl. 1</number>
      <electronic-resource-num>10.1002/joc.6704</electronic-resource-num>
      <urls>
        <related-urls>
          <url>https://www.documentation.ird.fr/hor/fdi:010079415</url>
        </related-urls>
        <pdf-urls>
          <url>https://www.documentation.ird.fr/intranet/publi/2020/08/010079415.pdf</url>
        </pdf-urls>
      </urls>
      <volume>41</volume>
      <remote-database-provider>Horizon (IRD)</remote-database-provider>
      <abstract>Numerous satellite-based precipitation datasets have been successively made available. Their precipitation estimates rely on clouds properties derived from microwave and thermal sensors in a so-named 'top-down' approach. Recently, a 'bottom-up' approach to infer precipitation from soil moisture (SM) estimates has resulted in the release of two new precipitation datasets (P-datasets). One uses satellite-based SM estimates from the European Spatial Agency (ESA) Climate Change Initiative (CCI) (SM2RAIN-CCI) while the other uses satellite-based SM from European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Advanced SCATterometer (ASCAT) (SM2RAIN-ASCAT). This study assesses SM2RAIN-ASCAT and -CCI reliability over two arid regions: Bolivian and Peruvian Altiplano and Pakistan (South Asia) using (a) direct comparisons with rain gauges and (b) testing the sensitivity of streamflow modelling to the P-datasets. Selecting two different regions and different indicators helps to assess whether the P-dataset reliability varies depending on the assessment method and location. For comparison purposes, the most reliable P-datasets from the literature are also considered (IMERG-E v.6, IMERG-L v.6, IMERG-F v.6, CHIRPS v.2 and MSWEP v.2.2). Compared to rain gauge observations and based on the modified Kling-Gupta Efficiency (KGE) values, the SM2RAIN-ASCAT and -CCI are more accurate in the Altiplano than in Pakistan. This difference is explained by a more favourable physical context for satellite-based SM estimates in the Altiplano. Over the Altiplano and despite an overall positive bias, SM2RAIN-ASCAT describes rain gauges temporal dynamics as well as IMERG-F v.6, CHIRPS v.2 and MSWEP v.2.2 and provides streamflow simulations very close to those obtained when using IMERG-F v.6, CHIRPS v.2 and MSWEP v.2.2 as forcing data.</abstract>
      <custom6>062</custom6>
      <custom1>UR228</custom1>
      <custom7>Bolivie / Pakistan</custom7>
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