近年来,提出了一些求解约束优化分布控制问题的方法,其中最常用的方法是先离散偏微分方程,然后求解离散得到的线性方程组.文献中提出了一些Krylov子空间预处理方法用来求解该线性方程组.通过分析张晓莹等提出的块对角预处理矩阵(Zhang X...近年来,提出了一些求解约束优化分布控制问题的方法,其中最常用的方法是先离散偏微分方程,然后求解离散得到的线性方程组.文献中提出了一些Krylov子空间预处理方法用来求解该线性方程组.通过分析张晓莹等提出的块对角预处理矩阵(Zhang X Y,Yan H Y.Huang Y M.On preconditionedMINRES method for solving the distributed control problems.Commun Appl Math Comput,2014,28:128-132.),构造了一个含参数的块对角预处理线性方程组,并运用含参数预处理最小残量方法求解该线性方程组.预处理矩阵的谱分析表明当参数大于1时,含参预处理线性方程组的谱分布更加集中.数值实验结果验证了含参数的预处理最小残量方法对于求解分布式控制问题是有效的.展开更多
The sensitivity of a regional climate model (RCM) to cumulus parameterization (CUPA) schemes in modeling summer precipitation over East Asia has been investigated by using the fifth-generation Pennsylvania State U...The sensitivity of a regional climate model (RCM) to cumulus parameterization (CUPA) schemes in modeling summer precipitation over East Asia has been investigated by using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (PSU-NCAR MM5). The feasibility of physical ensemble and the effect of interior (spectral) nudging are also assessed. The RCM simulations are evaluated against the NCEP/NCAR reanalysis data and NCEP/CPC precipitation data for three summers (JJA) in 1991, 1998, and 2003. The results show that the RCM is highly sensitive to CUPA schemes. Different CUPA schemes cause distinctive characteristics in the modeling of JJA precipitation and the intraseasonal (daily) variability of regional precipitation. The sensitivity of the RCM simulations to the CUPA schemes is reduced by adopting the spectral nudging technique, which enables the RCM to reproduce more realistic large-scale circulations at the upper levels of the atmosphere as well as near the surface, and better precipitation simulation in the selected experiments. The ensemble simulations using different CUPA schemes show higher skills than individual members for both control runs and spectral nudging runs. The physical ensemble adopting the spectral nudging technique shows the highest downscaling skill in capturing the general circulation patterns for all experiments and improved temporal distributions of precipitation in some regions.展开更多
基金Project supported by the National Natural Science Foundation of China(11571156)
文摘近年来,提出了一些求解约束优化分布控制问题的方法,其中最常用的方法是先离散偏微分方程,然后求解离散得到的线性方程组.文献中提出了一些Krylov子空间预处理方法用来求解该线性方程组.通过分析张晓莹等提出的块对角预处理矩阵(Zhang X Y,Yan H Y.Huang Y M.On preconditionedMINRES method for solving the distributed control problems.Commun Appl Math Comput,2014,28:128-132.),构造了一个含参数的块对角预处理线性方程组,并运用含参数预处理最小残量方法求解该线性方程组.预处理矩阵的谱分析表明当参数大于1时,含参预处理线性方程组的谱分布更加集中.数值实验结果验证了含参数的预处理最小残量方法对于求解分布式控制问题是有效的.
基金Supported by the "973" National Basic Research Program of China under Grant Nos. 2011CB952004 and 2006CB400500the National Natural Science Foundation of China under Grant Nos. 40705029 and 40830639
文摘The sensitivity of a regional climate model (RCM) to cumulus parameterization (CUPA) schemes in modeling summer precipitation over East Asia has been investigated by using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (PSU-NCAR MM5). The feasibility of physical ensemble and the effect of interior (spectral) nudging are also assessed. The RCM simulations are evaluated against the NCEP/NCAR reanalysis data and NCEP/CPC precipitation data for three summers (JJA) in 1991, 1998, and 2003. The results show that the RCM is highly sensitive to CUPA schemes. Different CUPA schemes cause distinctive characteristics in the modeling of JJA precipitation and the intraseasonal (daily) variability of regional precipitation. The sensitivity of the RCM simulations to the CUPA schemes is reduced by adopting the spectral nudging technique, which enables the RCM to reproduce more realistic large-scale circulations at the upper levels of the atmosphere as well as near the surface, and better precipitation simulation in the selected experiments. The ensemble simulations using different CUPA schemes show higher skills than individual members for both control runs and spectral nudging runs. The physical ensemble adopting the spectral nudging technique shows the highest downscaling skill in capturing the general circulation patterns for all experiments and improved temporal distributions of precipitation in some regions.