Three-dimensional variational assimilation method for satellite observation data considering channel correlation

A technology of satellite observation and three-dimensional variation, which is applied in measuring devices, weather condition forecasting, meteorology, etc., and can solve problems that are difficult to consider related to satellite observation data channels

Active Publication Date: 2019-01-15
NAT UNIV OF DEFENSE TECH
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[0004] The purpose of the present invention is to provide a three-dimensional variational assimilation method of satellite observation data considering channel correlation, so as to solve t

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  • Three-dimensional variational assimilation method for satellite observation data considering channel correlation
  • Three-dimensional variational assimilation method for satellite observation data considering channel correlation
  • Three-dimensional variational assimilation method for satellite observation data considering channel correlation

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[0023] In order to better understand the technical content of the present invention, specific embodiments are given together with the attached drawings for description as follows.

[0024] Aspects of the invention are described in this disclosure with reference to the accompanying drawings, which show a number of illustrated embodiments. Embodiments of the present disclosure are not necessarily intended to include all aspects of the invention. It should be appreciated that the various concepts and embodiments described above, as well as those described in more detail below, can be implemented in any of numerous ways, since the concepts and embodiments disclosed herein are not limited to any implementation. In addition, some aspects of the present disclosure may be used alone or in any suitable combination with other aspects of the present disclosure.

[0025] In order to consider the channel correlation of satellite observation data in data assimilation, the WRFVDA v3.7 thre...

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Abstract

The invention provides a three-dimensional variational assimilation method for satellite observation data considering channel correlation. The method comprises the following steps: 1) diagnosing channel correlation and an error standard deviation of satellite observation errors by using posterior information; 2) performing diagonalization decomposition on satellite observation error covariance matrix block; 3) inversing the satellite observation error covariance matrix block; 4) constructing a three-dimensional variational assimilation cost function considering channel correlation of the satellite observation data; 5) solving the constructed cost function and a gradient thereof by using a conjugate gradient minimization algorithm, and obtaining an optimal analysis field; and 6) testing theconvergence of the constructed three-dimensional variational assimilation method. According to the method, the channel correlation and error standard deviation of the satellite observation data are diagnosed by using the posterior information, an observation error covariance matrix in three-dimensional variational assimilation is constructed, and a matrix inversion method is designed, thereby solving the problem that the correlation between satellite observation data channels is not considered in current three-dimensional variational assimilation.

Description

technical field [0001] The invention belongs to the technical field of numerical weather prediction, and in particular relates to a three-dimensional variation assimilation method of satellite observation data considering channel correlation. Background technique [0002] Numerical weather prediction is a typical initial boundary value problem of differential equations. Improving the accuracy of numerical weather prediction requires improving the forecast model on the one hand, and improving the initial conditions of the model on the other hand. With the improvement of the numerical prediction model, the accuracy of the initial field of the model has become a key factor affecting the quality of the numerical prediction. In numerical weather prediction, the dimension of the atmospheric state variables in the governing equations exceeds 10 7 , and the number of observation samples of the atmospheric state in each 6-hour interval is 10 6 . Data assimilation improves the ini...

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Application Information

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IPC IPC(8): G01W1/10
CPCG01W1/10
Inventor 程小平王挺黄小刚费建芳丁菊丽
Owner NAT UNIV OF DEFENSE TECH
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