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      <src>https://socictopen.socict.org/files/original/a4080e021fe3318eb0f1647ea85008ea.pdf</src>
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            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>Coronavirus</text>
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            <name>Description</name>
            <description>An account of the resource</description>
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                <text>Dominio científico: Coronavirus</text>
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    <name>Text</name>
    <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
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      <name>Dublin Core</name>
      <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
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          <name>Title</name>
          <description>A name given to the resource</description>
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              <text>1D-Var multilayer assimilation of X-band SAR data into a detailed snowpack model</text>
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          <name>Creator</name>
          <description>An entity primarily responsible for making the resource</description>
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            <elementText elementTextId="216">
              <text>X. V. Phan, L. Ferro-Famil, M. Gay, Y. Durand, M. Dumont, S. Morin, S. Allain, G. D'Urso, A. Girard</text>
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          <name>Description</name>
          <description>An account of the resource</description>
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              <text>The structure and physical properties of a snowpack and their temporal evolution may be simulated using meteorological data and a snow metamorphism model. Such an approach may meet limitations related to potential divergences and accumulated errors, to a limited spatial resolution, to wind or topography-induced local modulations of the physical properties of a snow cover, etc. Exogenous data are then required in order to constrain the simulator and improve its performance over time. Synthetic-aperture radars (SARs) and, in particular, recent sensors provide reflectivity maps of snow-covered environments with high temporal and spatial resolutions. The radiometric properties of a snowpack measured at sufficiently high carrier frequencies are known to be tightly related to some of its main physical parameters, like its depth, snow grain size and density. SAR acquisitions may then be used, together with an electromagnetic backscattering model (EBM) able to simulate the reflectivity of a snowpack from a set of physical descriptors, in order to constrain a physical snowpack model. In this study, we introduce a variational data assimilation scheme coupling TerraSAR-X radiometric data into the snowpack evolution model Crocus. The physical properties of a snowpack, such as snow density and optical diameter of each layer, are simulated by Crocus, fed by the local reanalysis of meteorological data (SAFRAN) at a French Alpine location. These snowpack properties are used as inputs of an EBM based on dense media radiative transfer (DMRT) theory, which simulates the total backscattering coefficient of a dry snow medium at X and higher frequency bands. After evaluating the sensitivity of the EBM to snowpack parameters, a 1D-Var data assimilation scheme is implemented in order to minimize the discrepancies between EBM simulations and observations obtained from TerraSAR-X acquisitions by modifying the physical parameters of the Crocus-simulated snowpack. The algorithm then re-initializes Crocus with the modified snowpack physical parameters, allowing it to continue the simulation of snowpack evolution, with adjustments based on remote sensing information. This method is evaluated using multi-temporal TerraSAR-X images acquired over the specific site of the Argentière glacier (Mont-Blanc massif, French Alps) to constrain the evolution of Crocus. Results indicate that X-band SAR data can be taken into account to modify the evolution of snowpack simulated by Crocus.</text>
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          <name>Date</name>
          <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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            <elementText elementTextId="218">
              <text>2014</text>
            </elementText>
          </elementTextContainer>
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        <element elementId="43">
          <name>Identifier</name>
          <description>An unambiguous reference to the resource within a given context</description>
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            <elementText elementTextId="219">
              <text>DOI: 10.5194/tc-8-1975-2014</text>
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        <element elementId="48">
          <name>Source</name>
          <description>A related resource from which the described resource is derived</description>
          <elementTextContainer>
            <elementText elementTextId="220">
              <text>The Cryosphere</text>
            </elementText>
          </elementTextContainer>
        </element>
        <element elementId="45">
          <name>Publisher</name>
          <description>An entity responsible for making the resource available</description>
          <elementTextContainer>
            <elementText elementTextId="221">
              <text>Copernicus Publications</text>
            </elementText>
          </elementTextContainer>
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          <name>Coverage</name>
          <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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            <elementText elementTextId="222">
              <text>Environmental sciences, Geology</text>
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          </elementTextContainer>
        </element>
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          <name>Language</name>
          <description>A language of the resource</description>
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            <elementText elementTextId="223">
              <text>EN</text>
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