THE EFFECTIVENESS OF GENETIC ALGORITHM IN CAPTURING CONDITIONAL NONLINEAR OPTIMAL PERTURBATION WITH PARAMETERIZATION ON-

In the typhoon adaptive observation based on conditional nonlinear optimal perturbation (CNOP),the 'on-off' switch caused by moist physical parameterization in prediction models prevents the conventional adjoint method from providing correct gradient during the optimization process. To address this problem,the capture of CNOP,when the "on-off' switches are included in models,is treated as non-smooth optimization in this study,and the genetic algorithm (GA) is introduced. After detailed algorithm procedures are formulated using an idealized model with parameterization "'on-off" switches in the tbrcing term,the impacts of "on-off' switches on the capture of CNOP are analyzed,and three numerical experiments are conducted to check the effectiveness of GA in capturing CNOP and to analyze the impacts of different initial populations on the optimization result. The result shows that GA is competent for the capture of CNOP in the context of the idealized model with parameterization 'on-off' switches in this study. Finally,the advantages and disadvantages of GA in capturing CNOP are analyzed in detail.

作 者： FANG Chang-luan ZHENG Qin   作者單位： FANG Chang-luan(Institute of Science,PLA University of Science and Technology,Nanjing 211101;Oceanic Hydrometeorological Center of the South Sea Navy Fleet,Zhanjiang 524001)

ZHENG Qin(Institute of Science,PLA University of Science and Technology,Nanjing 211101) 

刊 名： 熱帶氣象學(xué)報(bào)(英文版)  英文刊名： JOURNAL OF TROPICAL METEOROLOGY  年，卷(期)： 2009 15(1)  分類號(hào)： P456  關(guān)鍵詞： dynamic meteorology   typhoon adaptive observation   genetic algorithm   conditional nonlinear optimal perturbation   switches   moist physical parameterization