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          <dc:title>Meghna Mistri: SMALL NEIGHBOURHOODS, BETTER FORECASTS</dc:title>
          <dc:creator>Meghna Mistri (15951311)</dc:creator>
          <dc:creator>Lauren Smith (9937769)</dc:creator>
          <dc:creator>Vivien Kirk (1220007)</dc:creator>
          <dc:subject>Dynamical systems in applications</dc:subject>
          <dc:subject>data assimilation</dc:subject>
          <dc:subject>localisation</dc:subject>
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          <dc:description>&lt;p dir="ltr"&gt;Data assimilation is a method that combines a model with measurements to obtain an improved forecast. Finite ensemble-based DA methods often have the problem of spurious correlations, which leads to states of the model being combined with unrelated measurements. Localisation constricts the range of measurements that can affect the forecast at a point and improves the quality of the forecast.&lt;/p&gt;</dc:description>
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