Improvements of One-dimensional Variational Assimilation Algorithm in Occultation Technique

Statistics – Computation

Scientific paper

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Earth, Atmospheric Effects, Techniques: Miscellaneous, Methods: Numerical, Miscellaneous

Scientific paper

The vertical profiles of water vapor and temperature retrieved from GPS/LEO occultation data are potentially valuable data source for the meteorological and atmospheric science. The assimilation of GPS/LEO occultation data may effectively improve the vertical profiles and hence improve the accuracy of the current numerical weather prediction (NWP). At present, the largest problem for applying variational assimilation retrieval technique to the current NWP model is the enormous computation. By the improvements of cost function of one-dimensional variational assimilation and the re-design of iteration process, the new algorithm adopted in this paper avoids repeated calculations of large dimensional matrix. Therefore, the computational efficiency of variational assimilation can be improved. In the numerical simulation discussion, the retrieval results from CHAMP occultation refractivity profile is tested when taking ECMWF analytical model added the Gaussian white noise as the true value.

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