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    <titleInfo>
      <title>Combining scintillometer measurements and an aggregation scheme to estimate area-averaged latent heat flux during the AMMA experiment</title>
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      <namePart type="family">Ezzahar</namePart>
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      <namePart type="family">Chehbouni</namePart>
      <namePart type="given">Abdelghani</namePart>
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      <namePart type="family">Hoedjes</namePart>
      <namePart type="given">Johannes</namePart>
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      <namePart type="family">Ramier</namePart>
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      <namePart type="family">Boulain</namePart>
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      <namePart type="family">Mougenot</namePart>
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    <abstract>This paper deals with the issue of using scintillometry in conjunction with a simple aggregation scheme to derive area-averaged sensible and latent heat fluxes over a small watershed in Niamey, Niger (Wankama catchment). Data collected in the context of the African Monsoon Multidisciplinary Analysis (AMMA) program has been used to test the proposed approach. For this purpose, a Large Aperture Scintillometer (LAS) was set up over heterogeneous surface transect of about 3.2 km spanning three vegetation types. The comparison between scintillometer-based estimates of area-averaged sensible heat fluxes and those measured by a network of the classical eddy covariance (EC) devices showed good agreement. with a relative error of about 20% (R-2 = 0.85, RMSD = 22 W m(-2), and SEE = 21.39 W m(-2)). This is a good result considering the contrast in terms of the footprint scales associated with the two devices, which is amplified by the heterogeneity of the catchment. The results also showed that using the LAS-derived values of area-average sensible heat flux in conjunction with a simple aggregation rule to estimate area-average available energy led to a reasonable prediction of area-averaged latent heat flux (R-2 = 0.75, RMSD = 64 W m(-2) and SEE = 50 W m(-2)), when compared to those measured using the EC network. This is of interest since the LAS can potentially be used to validate estimates of surface fluxes, based on the meso-scale model, as well as those estimated using coarse-scale remote sensing-based algorithm.</abstract>
    <targetAudience authority="marctarget">specialized</targetAudience>
    <subject>
      <topic>Scintillometry</topic>
      <topic>Eddy covariance</topic>
      <topic>Regional surfaces fluxes</topic>
      <topic>Non-uniform and heterogeneous surfaces</topic>
      <topic>Aggregation schemes</topic>
    </subject>
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      <titleInfo>
        <title>Journal of Hydrology</title>
      </titleInfo>
      <part>
        <detail type="volume">
          <number>375</number>
        </detail>
        <detail type="volume">
          <number>1-2</number>
        </detail>
        <extent unit="pages">
          <list> 217-226</list>
        </extent>
      </part>
      <originInfo>
        <dateIssued>2009</dateIssued>
      </originInfo>
      <identifier type="issn">0022-1694</identifier>
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    <identifier type="uri">https://www.documentation.ird.fr/hor/fdi:010048240</identifier>
    <identifier type="doi">10.1016/j.jhydrol.2009.01.010</identifier>
    <identifier type="issn">0022-1694</identifier>
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      <recordCreationDate encoding="w3cdtf">2009-11-09</recordCreationDate>
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