Impact of Analysis-time Tuning on the Performance of the DRP-4DVar Approach |
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| Authors: | ZHAO Juan WANG Bin and LIU Juanjuan |
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| Institution: | 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 dimensional
variational data assimilation (DRP-4DVar) approach to allow the analysis
time to be tunable, so that the intervals between analysis time and
observation times can be shortened. Due to the limits of the perfect-model
assumption and the tangent-linear hypothesis, the analysis-time tuning is
expected to have the potential to further improve analyses and forecasts.
Various sensitivity experiments using the Lorenz-96 model are conducted to
test the impact of analysis-time tuning on the performance of the new
approach 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 that
the scheme with the analysis time in the middle of the window outperforms
the others, on the whole. Moreover, the advantage of this scheme is more
pronounced when a longer assimilation window is adopted or more observations
are assimilated. |
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| Keywords: | DRP-4DVar analysis-time tuning perfect-model assumption tangent-linear hypothesis |
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