Impact of Analysis-time Tuning on the Performance of the DRP-4DVar Approach |
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| Authors: | ZHAO Juan WANG Bin LIU Juanjuan |
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| Affiliation: | State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, Graduate University of the Chinese Academy of Sciences, Beijing 100049,State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029 |
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| Abstract: | In this study we extend the dimension-reduced projection-four dimensionalvariational data assimilation (DRP-4DVar) approach to allow the analysistime to be tunable, so that the intervals between analysis time andobservation times can be shortened. Due to the limits of the perfect-modelassumption and the tangent-linear hypothesis, the analysis-time tuning isexpected to have the potential to further improve analyses and forecasts.Various sensitivity experiments using the Lorenz-96 model are conducted totest the impact of analysis-time tuning on the performance of the newapproach under perfect and imperfect model scenarios, respectively.Comparing three DRP-4DVar schemes having the analysis time at the start,middle, and end of the assimilation window, respectively, it is found thatthe scheme with the analysis time in the middle of the window outperformsthe others, on the whole. Moreover, the advantage of this scheme is morepronounced when a longer assimilation window is adopted or more observationsare assimilated. |
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| Keywords: | DRP-4DVar analysis-time tuning perfect-model assumption tangent-linear hypothesis |
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