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    <titleInfo>
      <title>Ensemble precipitation estimates based on an assessment of 21 gridded precipitation datasets to improve precipitation estimations across Madagascar</title>
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    <abstract>Study region: this study focuses on Madagascar. This island is characterized by a great diversity of climate, due to trade winds and the varying topography. This country is also undergoing extreme rainfall events such as droughts and cyclones. Study focus: the rain gauge network of Madagascar is limited (about 30 stations). Consequently, we consider relevant satellite-based precipitation datasets to fill gaps in ground-based datasets. We assessed the reliability of 21 satellite-based and reanalysis precipitation products (P-datasets) through a direct comparison with 24 rain gauge station measurements at the monthly time step, using four statistical indicators: Kling-Gupta Efficiency (KGE), Correlation Coefficient (CC), Root Mean Square Error (RMSE), and Bias. Based on this first analysis, we produced a merged dataset based on a weighted average of the 21 products. New hydrological insights for the region: based on the KGE and the CC scores, WFDEI (WATCH Forcing Data methodology applied to ERA-Interim), CMORPH-BLD (Climate Prediction Center MORPHing satellite-gauge merged) and MSWEP (Multi-Source Weighted Ensemble Precipitation) are the most accurate for estimating rainfall at the national scale. Additionally, the results reveal a high discrepancy between bio-climatic regions. The merged dataset reveals higher performance than the other products in all situations. These results demonstrate the usefulness of a merging approach in an area with a deficit of rainfall data and a climatic and topographic diversity.</abstract>
    <targetAudience authority="marctarget">specialized</targetAudience>
    <subject>
      <topic>Precipitation products</topic>
      <topic>Remote sensing</topic>
      <topic>Ensemble approach</topic>
      <topic>Hydrology</topic>
      <topic>Madagascar</topic>
    </subject>
    <subject authority="local">
      <geographic>MADAGASCAR</geographic>
    </subject>
    <classification authority="local">062</classification>
    <classification authority="local">126</classification>
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      <titleInfo>
        <title>Journal of Hydrology : Regional Studies</title>
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      <part>
        <detail type="volume">
          <number>47</number>
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        <extent unit="pages">
          <list> 101400 [20 p.]</list>
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      <originInfo>
        <dateIssued>2023</dateIssued>
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    <identifier type="uri">https://www.documentation.ird.fr/hor/fdi:010090021</identifier>
    <identifier type="doi">10.1016/j.ejrh.2023.101400</identifier>
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      <recordCreationDate encoding="w3cdtf">2023-09-22</recordCreationDate>
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