| 条件非线性最优扰动方法在适应性观测研究中的初步应用 |
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| 引用本文： | 穆穆,王洪利,周菲凡.条件非线性最优扰动方法在适应性观测研究中的初步应用[J].大气科学,2007,31(6):1102-1112. |
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| 作者姓名： | 穆穆 王洪利 周菲凡 |
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| 作者单位： | 1.中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室,北京,100029 |
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| 基金项目： | 中国科学院知识创新工程重要方向项目KZCX3-SW-230，国家自然科学基金NO.40675030 |
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| 摘 要： | 针对适应性观测中敏感性区域的确定问题，考虑初始误差对预报结果的影响, 比较了条件非线性最优扰动(CNOP)与第一线性奇异向量(FSV)在两个降水个例中的空间结构的差异，考察了它们总能量范数随时间发展演变的异同。结合敏感性试验的分析，揭示了预报结果对CNOP类型的初始误差的敏感性要大于对FSV类型的初始误差的敏感性，因而减少初值中CNOP类型误差的振幅比减少FSV类型的收益要大。这一结果表明可以把CNOP方法应用于适应性观测来识别大气的敏感区。关于将CNOP方法有效地应用于适应性观测所面临的挑战及需要采取的对策等也进行了讨论。
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| 关 键 词： | 适应性观测 敏感性区域 条件非线性最优扰动 第一奇异向量 |
| 文章编号： | 1006-9895（2007）06-1102-11 |
| 修稿时间： | 2007-05-30 |
A Preliminary Application of Conditional Nonlinear Optimal Perturbation to Adaptive Observation |
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| MU Mu,WANG Hong-Li and ZHOU Fei-Fan.A Preliminary Application of Conditional Nonlinear Optimal Perturbation to Adaptive Observation[J].Chinese Journal of Atmospheric Sciences,2007,31(6):1102-1112. |
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| Authors: | MU Mu WANG Hong-Li and ZHOU Fei-Fan |
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| Institution: | 1 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmos- pheric Physics, Chinese Academy of Sciences, Beijing 100029 2 Graduate University of Chinese Academy of Sciences, Beijing 100049 3 Laboratory of Cloud-Precipitation Physics and Severe Storms, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029 |
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| Abstract: | This study is concerned with!the applicability of conditional optimal perturbation(CNOP) to the determination of sensitivity area in adaptive observation.MM5(Mesoscale Model 5) model and its adjoint form are utilized to study the effects of initial errors on the forecasts of two precipitation cases in July 2003 and in August 1996.The authors compare the differences between the structures of the conditional nonlinear optimal perturbations(CNOPs) and the first linear singular vectors(FSVs),and calculate the developments of their total energies.It is found that the structures of CNOPs differ much from those of FSVs as well as the developments of their total energies.The results of sensitivity experiments indicate that the forecast results are more sensitive to the CNOP-type initial errors than the FSV-type ones.This suggests that the forecast results benefit more from the reductions of the CNOP-type initial errors than the reductions of the FSV-type ones.This indicates that it is feasible to use CNOP for the determination of sensitivity area in adaptive observation.The authors also discuss the problems that may be confronted in applying CNOPs to adaptive observation and the potential solutions. |
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| Keywords: | adaptive observation sensitivity area Conditional Nonlinear Optimal Perturbation(CNOP) the first linear singular vector(FSV) |
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