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变分同化方法反演海气耦合模型参数的研究
引用本文:杜华栋,黄思训,蔡其发,程亮.变分同化方法反演海气耦合模型参数的研究[J].南京气象学院学报,2007,30(4):444-449.
作者姓名:杜华栋  黄思训  蔡其发  程亮
作者单位:1. 中国人民解放军理工大学,气象学院,江苏,南京,211101
2. 中国人民解放军理工大学,气象学院,江苏,南京,211101;南京信息工程大学,江苏省气象灾害重点实验室,江苏,南京,210044
3. 北京2433信箱,北京,100081
基金项目:国家自然科学基金资助项目(90411006,40575052)
摘    要:采用变分资料同化技术,结合最优控制思想,对一个海气耦合模型的模式参数和强迫项进行了反演。结果表明,采用该方法对模式进行优化,既可以补偿模式参数不准确性给预报带来的误差,又可以对模式参数本身进行修正和估计,为将来在实际应用中改善更复杂的预报模式、提高预报准确率提供了一个可借鉴的思路。

关 键 词:变分资料同化  海气耦合模型  最优控制
文章编号:1000-2022(2007)04-0444-06
修稿时间:2006-06-07

Variational Assimilation for a Coupled Air-Sea Model
DU Hua-dong,HUANG Si-xun,CAI Qi-fa,CHENG Liang.Variational Assimilation for a Coupled Air-Sea Model[J].Journal of Nanjing Institute of Meteorology,2007,30(4):444-449.
Authors:DU Hua-dong  HUANG Si-xun  CAI Qi-fa  CHENG Liang
Affiliation:1. Institute of Meteorology, PLA University of Science and Technology, Nanjing 211101, China 2. Jiangsu Key Laboratory of Meteorological Disaster,NUIST,Nanjing 210044,China; 3. Beijing POBox 2433, Beijing 100081, China
Abstract:For the prediction of ENSO,the accuracy of the model including the parameters and initial value etc is important,and they can be retrieved by the variational data assimilation methods developed in recent years.But when the nonlinearity of the model is strong enough,the effect of the improvement made by the 4-D variational data assimilation may be poor due to the bad approximation of the tangent linear model to the original model.So the idea of optimal control is introduced in the paper to improve the effect of 4-DVAR in the inversion of the parameters of a nonlinear dynamic ENSO model.The results indicate that when the terminal controlling term originated from the optimal control is added to the cost functional of 4DVAR,the effect of inversion might be obviously improved in comparison with the traditional 4DVAR,especially the phase orbit of model variables is obviously improved.The results in the paper also suggest that the method of 4DVAR in combination with optimal control can not only reduce the error resulted from the inaccuracy of the model parameters but also correct the parameters itself.This gives a good method for modifying the model and improving the quality of prediction of ENSO.
Keywords:variational data assimilation  coupled air-sea model  optimal control
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