中尺度模式遗传算法同化系统及同化试验研究

A Genetic Algorithm Assimilation System for Mesoscale Model and Its Assimilation Experiments

设计了一个以MM5模式为基础的遗传算法同化系统,并对一次暴雨过程进行了实际降水的模拟,通过对比遗传同化和伴随同化的降水预报效果,对遗传算法同化系统的同化性能进行验证。试验结果表明,遗传算法与四维变分相结合的同化系统能有效地改善模式的初始场,使MM5模式要素预报和降水预报的准确率得到提高。

In this paper, a genetic algorithm （GA）-based four-dimensional variational data assimilation （4DVAR） is applied to the MM5 model. In order to verify the performance of the GA assimilation system, the output of the GA based 4DVAR model has been compared with that of an adjoint 4DVAR model. The results indicate that the new method of GA-based 4DVAR can be considered as one of the effective methods to improve numerical weather prediction initial field and raise the prediction accuracy of physical field and rainfall. The new method shows a better performance than the adjoint counterpart based on the present experimental case.