条件非线性最优扰动方法在陆面过程模式参数优化中的扩展应用初探

本文旨在探讨条件非线性最优扰动(CNOP)方法在陆面过程模式的参数优化工作方面的扩展应用.使用通用陆面模式(CoLM)和CEOP地面基准站——吉林通榆站退化草地2006年生长季的资料,针对土壤颜色、砂土比例和叶面积指数等关键模式参数,使用感热通量、潜热通量和浅层土壤温湿度作为检测变量,设计了单参数和多参数优化试验.结果表明,CONP扩展方法得到的优化参数提高了CoLM对检测变量的模拟能力,并且多参数的优化结果明显优于单参数的优化结果,在模式模拟偏差较大的土壤湿度方面改进尤为显著,此外,使用了差异进化算法( 关键词： 条件非线性最优扰动(CNOP) 陆面过程模式 参数优化

Using conditional nonlinear optimal perturbation method in parameter optimization of land surface processes model

In this paper, we attempted to entend the application of conditional nonlinear optimal perturbation(CNOP) to the optimization of parameters in land surface model. We used the common land model and data of Tongyu station,which is a reference site of the CEOP in the semi-arid regions, and used three key parameters (soil color, soil sand/lay proportion and leaf area index) as parameters to be optimized. Two experiments are designed in our work, namely the single-parameter optimization and the triple-parameter optimization. Notable improvements in simulating sensible heat flux (SH), latent heat flux (LH), soil temperature (TS) and moisture (MS) at shallow layers were achieved by using the optimized parameters. In addition, the latter experiment shows a better performance than the former. All results above illustrate that the application of CNOP method can be extended to parameters optimization of land surface model. And what is more, due to its other advantages, such as the clear mathematical meaning, the simple design structure, and the fast computing speed, it shows a great potential for further applications in parameters optimization of related problems.