Data assimilation with correlated observation errors : experiments with a 1-D shallow water model

@inproceedings{Stewart2013DataAW,
  title={Data assimilation with correlated observation errors : experiments with a 1-D shallow water model},
  author={Laura F M Stewart and Sarah L. Dance and Nancy K. Nichols},
  year={2013}
}
Remote sensing observations often have correlated errors, but the correlations are typically ignored in data assimilation for numerical weather prediction. The assumption of zero correlations is often used with data thinning methods, resulting in a loss of information. As operational centres move towards higher-resolution forecasting, there is a requirement to retain data providing detail on appropriate scales. Thus an alternative approach to dealing with observation error correlations is… CONTINUE READING
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