Enhancing the ability of the WRF model in simulating a large area covering the West Pacific Ocean, China's Mainland, and the East Indian Ocean is very important to improve prediction of the East Asian monsoon clim...Enhancing the ability of the WRF model in simulating a large area covering the West Pacific Ocean, China's Mainland, and the East Indian Ocean is very important to improve prediction of the East Asian monsoon climate. The objective of this study is to identify a reasonable configuration of physical parameterization schemes to simulate the precipitation and temperature in this large area. The Mellor-Yamada-Janjic （MYJ） and Yonsei University （YSU） PBL schemes, the WSM3 and WSM5 microphysics schemes, and the Betts-Miller-Janjic （BMJ） and Tiedtke cumulus schemes are compared through simulation of the regional climate of summer 2008. All cases exhibit a similar spatial distribution of temperature as observed, and the spatial correlation coefficients are all higher than 0.95. The cases combining MY J, WSM3/WSM5, and BMJ have the smallest biases of temperature. The choice of PBL scheme has a significant effect on precipitation in such a large area. The cases with MYJ reproduce a better distribution of rain belts, while YSU strongly overestimates the precipitation intensity. The precipitation simulated using WSM3 is similar to that using WSM5. The BMJ cumulus scheme combined with the MYJ PBL scheme has a smaller bias of precipitation. However, the Tiedtke scheme reproduces the precipitation pattern better, especially over the ITCZ.展开更多
目的:检验数值天气预报模式(WRF)在雅砻江下游对强降水的预报能力,并找出表现最优的参数化方案组合。创新点:首次针对雅砻江流域检验WRF模式对强降水的预报能力,并加入了计算时间作为评价的重要参考。方法:通过三场强降水事件,利用七种...目的:检验数值天气预报模式(WRF)在雅砻江下游对强降水的预报能力,并找出表现最优的参数化方案组合。创新点:首次针对雅砻江流域检验WRF模式对强降水的预报能力,并加入了计算时间作为评价的重要参考。方法:通过三场强降水事件,利用七种常用的云微物理参数化方案(Kessler,Lin et al.(Lin),SingleMoment 3-class(WSM3),Single-Moment 5-class(WSM5),Ferrier,Single-Moment 6-class(WSM6),和New Thompson et al.(NTH))和3种积云对流参数化方案(Kain-Fritsch(KF),Betts-Miller-Janjic(BMJ)和Grell-Devenyi(GD))的组合,对WRF模式在雅砻江下游的降水预报能力进行检验。为了评价WRF模式的预报能力,引入探测率(POD),空报率(FAR),BIAS和公平预报评分(ETS),对比不同方案组合的降水空间分布和站点预报的有效性。同时,均方根误差(RMSE)等指标被用来评价面雨量预报的精确性。除常规评价外,还将计算时间作为方案评价的重要参考,在满足精度需求的前提下优先选择计算效率高的方案组合。结论:1.WRF模式能够适用于雅砻江下游强降水预报;2.WSM3以及GD参数化方案组合的表现最为有效和稳定。展开更多
基金funded by the National Natural Science Foundation of China[General Project,grant number 41275108]the Strategic Priority Research Program of the Chinese Academy of Sciences[grant number XDA11010404]
文摘Enhancing the ability of the WRF model in simulating a large area covering the West Pacific Ocean, China's Mainland, and the East Indian Ocean is very important to improve prediction of the East Asian monsoon climate. The objective of this study is to identify a reasonable configuration of physical parameterization schemes to simulate the precipitation and temperature in this large area. The Mellor-Yamada-Janjic （MYJ） and Yonsei University （YSU） PBL schemes, the WSM3 and WSM5 microphysics schemes, and the Betts-Miller-Janjic （BMJ） and Tiedtke cumulus schemes are compared through simulation of the regional climate of summer 2008. All cases exhibit a similar spatial distribution of temperature as observed, and the spatial correlation coefficients are all higher than 0.95. The cases combining MY J, WSM3/WSM5, and BMJ have the smallest biases of temperature. The choice of PBL scheme has a significant effect on precipitation in such a large area. The cases with MYJ reproduce a better distribution of rain belts, while YSU strongly overestimates the precipitation intensity. The precipitation simulated using WSM3 is similar to that using WSM5. The BMJ cumulus scheme combined with the MYJ PBL scheme has a smaller bias of precipitation. However, the Tiedtke scheme reproduces the precipitation pattern better, especially over the ITCZ.
基金Project supported by the National Natural Science Foundation of China(Nos.51109177 and 51209223)the Major National Science and Technology Program(No.2012ZX07205-005)+1 种基金the National Key Technology R&D Program of China during the"12th Five-Year Plan"(No.2013BAB05B01)the Doctoral Thesis Innovation Program of the China Institute of Water Resources and Hydropower Research
文摘目的:检验数值天气预报模式(WRF)在雅砻江下游对强降水的预报能力,并找出表现最优的参数化方案组合。创新点:首次针对雅砻江流域检验WRF模式对强降水的预报能力,并加入了计算时间作为评价的重要参考。方法:通过三场强降水事件,利用七种常用的云微物理参数化方案(Kessler,Lin et al.(Lin),SingleMoment 3-class(WSM3),Single-Moment 5-class(WSM5),Ferrier,Single-Moment 6-class(WSM6),和New Thompson et al.(NTH))和3种积云对流参数化方案(Kain-Fritsch(KF),Betts-Miller-Janjic(BMJ)和Grell-Devenyi(GD))的组合,对WRF模式在雅砻江下游的降水预报能力进行检验。为了评价WRF模式的预报能力,引入探测率(POD),空报率(FAR),BIAS和公平预报评分(ETS),对比不同方案组合的降水空间分布和站点预报的有效性。同时,均方根误差(RMSE)等指标被用来评价面雨量预报的精确性。除常规评价外,还将计算时间作为方案评价的重要参考,在满足精度需求的前提下优先选择计算效率高的方案组合。结论:1.WRF模式能够适用于雅砻江下游强降水预报;2.WSM3以及GD参数化方案组合的表现最为有效和稳定。
