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中国物理学会期刊

正则化方法同化多普勒天气雷达资料及对降雨预报的影响

CSTR: 32037.14.aps.60.079202

Regularization method of assimilating Doppler radar data and its influence on precipitation forecast

CSTR: 32037.14.aps.60.079202
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  • 基于三维变分同化(3DVAR)的思想,提出一种适用于多普勒天气雷达资料直接同化的正则化方法.从寻求Yo=H(X)带有偏差δ的极小模解出发,引入正则化思想,并给出与3DVAR方案不同的新代价函数.针对2008年8月14日发生在北京地区的一次局地暴雨过程,设计了一组数值试验,并采用L曲线准则后验选取最优正则化参数.数值结果表明:正则化方法和3DVAR方案均能有效同化多普勒雷达资料,雷达径向速度的同化效果明显好于反射率因

     

    A new regularization method is proposed to directly assimilate Doppler radar data into mesoscale numerical weather forecast based on the traditional 3DVAR. For seeking the minimum module solution of the Yo=H(X) with bias δ, the regularization method is adopted and leads to a new cost function. A group of experiments were designed to study the case of a locally strong rainstorm occurred in Beijing area on August 14, 2008. The L-curve principle is used to determine the optimal regularization parameter and the result is α=0.1. Numerical results demonstrate that both regularization method and 3DVAR scheme can efficiently assimilate the Doppler radar data, and that the improved initial condition can alleviate the spin-up phenomenon and improve the nowcasting precipitation forecast. However, when an optimal regularization parameter is choser, better improvement, more accurate precipitation forecast and higher TS score are expected.

     

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