DOI: 10.1007/s00382-017-3729-3
Scopus记录号: 2-s2.0-85019259715
论文题名: Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area
作者: Di Z. ; Duan Q. ; Wang C. ; Ye A. ; Miao C. ; Gong W.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2018
卷: 50, 期: 2018-05-06 起始页码: 1927
结束页码: 1948
语种: 英语
英文关键词: Adaptive surrogate model-based optimization method
; Optimization assessment
; Parameter optimization
; Weather Research and Forecasting model
Scopus关键词: boundary condition
; climate modeling
; optimization
; parameterization
; precipitation (climatology)
; spatial resolution
; summer
; weather forecasting
; Beijing [China]
; China
英文摘要: Forecasting skills of the complex weather and climate models have been improved by tuning the sensitive parameters that exert the greatest impact on simulated results based on more effective optimization methods. However, whether the optimal parameter values are still work when the model simulation conditions vary, which is a scientific problem deserving of study. In this study, a highly-effective optimization method, adaptive surrogate model-based optimization (ASMO), was firstly used to tune nine sensitive parameters from four physical parameterization schemes of the Weather Research and Forecasting (WRF) model to obtain better summer precipitation forecasting over the Greater Beijing Area in China. Then, to assess the applicability of the optimal parameter values, simulation results from the WRF model with default and optimal parameter values were compared across precipitation events, boundary conditions, spatial scales, and physical processes in the Greater Beijing Area. The summer precipitation events from 6 years were used to calibrate and evaluate the optimal parameter values of WRF model. Three boundary data and two spatial resolutions were adopted to evaluate the superiority of the calibrated optimal parameters to default parameters under the WRF simulations with different boundary conditions and spatial resolutions, respectively. Physical interpretations of the optimal parameters indicating how to improve precipitation simulation results were also examined. All the results showed that the optimal parameters obtained by ASMO are superior to the default parameters for WRF simulations for predicting summer precipitation in the Greater Beijing Area because the optimal parameters are not constrained by specific precipitation events, boundary conditions, and spatial resolutions. The optimal values of the nine parameters were determined from 127 parameter samples using the ASMO method, which showed that the ASMO method is very highly-efficient for optimizing WRF model parameters. © 2017, Springer-Verlag Berlin Heidelberg. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/109398
Appears in Collections: 影响、适应和脆弱性 气候变化事实与影响
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作者单位: State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China; Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China
Recommended Citation:
Di Z.,Duan Q.,Wang C.,et al. Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area[J]. Climate Dynamics,2018-01-01,50(2018-05-06)