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- W2164607079 abstract "Abstract A challenging problem in numerical weather prediction is to optimize the use of meteorological observations in data assimilation. Even assimilation techniques considered “optimal” in the “least squares” sense usually involve a set of assumptions that prescribes the horizontal and vertical distributions of analysis increments used to update the background analysis. These assumptions may impose limitations on the use of the data that can adversely affect the data assimilation and any subsequent forecast. Virtually all widely used operational analysis and dynamic-initialization techniques assume, at some level, that the errors are isotropic and so the data can be applied within circular regions of influence around measurement sites. Whether implied or used directly, circular isotropic regions of influence are indiscriminate toward thermal and wind gradients that may reflect changes of air mass. That is, the analytic process may ignore key flow-dependent information available about the physical error..." @default.
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- W2164607079 date "2001-04-01" @default.
- W2164607079 modified "2023-09-28" @default.
- W2164607079 title "A Heuristic Study on the Importance of Anisotropic Error Distributions in Data Assimilation" @default.
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- W2164607079 doi "https://doi.org/10.1175/1520-0493(2001)129<0766:ahsoti>2.0.co;2" @default.
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