Open AccessRegularization method of assimilating Doppler radar data and its influence on precipitation forecast
Author(s) -
Yue Zhao,
Huang Si-Xun,
Du Hua-Dong,
Zhong Ji-Qin
Publication year - 2011
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.60.079202
Subject(s) - regularization (linguistics) , radar , nowcasting , doppler radar , mesoscale meteorology , doppler effect , computer science , quantitative precipitation forecast , meteorology , algorithm , precipitation , mathematics , remote sensing , geology , physics , artificial intelligence , telecommunications , astronomy
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.