| GRAPES_MESO中时间步长和空间分辨率对于预报效果的影响 |
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| 引用本文： | 刘德强,冯杰,李建平,王金成.GRAPES_MESO中时间步长和空间分辨率对于预报效果的影响[J].大气科学,2015,39(6):1165-1178. |
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| 作者姓名： | 刘德强 冯杰 李建平 王金成 |
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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;中国科学院大学, 北京 100049;福建省气象台, 福州 350001 |
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| 基金项目： | 国家自然科学基金项目41375110、41175069 |
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| 摘 要： | 基于GRAPES区域中尺度数值预报系统(GRAPES_MESO),针对700 hPa、500 hPa和200 hPa的位势高度场H,温度场T,风场纬向分量U,经向分量V和地面降水场,在给定的模式物理过程下,分别考察了时间步长和空间分辨率对于模式预报效果的影响。研究结果表明,空间分辨率(0.3°×0.3°)相同时,各变量在不同层次的预报几乎都存在最优时间步长使得预报技巧最高,初步说明最优时间步长理论在复杂的偏微分方程组中的适用性。随后,将空间分辨率为0.3°×0.3°时最优时间步长(240 s)的预报结果与当前业务中(空间分辨率为0.15°×0.15°、时间步长为90 s)的预报结果进行比较,发现前者的变量H、T、U、V和地面降水场的预报技巧均高于后者,表明并不是空间分辨率越高预报效果越好。
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| 关 键 词： | GRAPES_MESO 时间步长 空间分辨率 预报效果 |
| 收稿时间： | 2014/11/2 0:00:00 |
| 修稿时间： | 2015/1/29 0:00:00 |
The Impacts of Time-Step Size and Spatial Resolution on the Prediction Skill of the GRAPES-MESO Forecast System |
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| LIU Deqiang,FENG Jie,LI Jianping and WANG Jincheng.The Impacts of Time-Step Size and Spatial Resolution on the Prediction Skill of the GRAPES-MESO Forecast System[J].Chinese Journal of Atmospheric Sciences,2015,39(6):1165-1178. |
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| Authors: | LIU Deqiang FENG Jie LI Jianping and WANG Jincheng |
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| Institution: | State Key Laboratory of Numerical Modeling for Atmospheric Science and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;University of Chinese Academy of Sciences, Beijing 100049;Fujian Meteorological Observatory, Fuzhou 350001,State Key Laboratory of Numerical Modeling for Atmospheric Science and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;University of Chinese Academy of Sciences, Beijing 100049,College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875;Joint Center for Global Change Studies, Beijing 100875 and Numerical Weather Prediction Center of China Meteorological Administration, Beijing 100081 |
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| Abstract: | This study considered the impacts of time-step size and spatial resolution on the prediction skill of the Global/Regional Assimilation and Prediction System(GRAPES) mesoscale numerical forecast system(GRAPES-MESO) for a given parameter set. The forecasts of geopotential height(H), temperature(T), and the zonal(U) and meridional(V) components of wind at 700, 500, and 200 hPa, were assessed, as well as surface precipitation. The results showed that, at a spatial resolution of 0.3°×0.3°, the prediction skill of almost all variables, including H, T, U and V, in the three vertical layers were optimized at a particular time step of approximately 240 s. This raises the possibility of an optimal time-step size for a particular spatial resolution, and the explanation for this relationship might be related to the computational uncertainty principle. The operational forecasts based on a spatial resolution of 0.15°×0.15° and a time-step size of 90 s were also compared with the best results obtained previously, in which the spatial resolution was 0.3°×0.3° and the time step was 240 s. The latter configuration possessed higher skill than the operational forecasts for all variables, indicating that the prediction quality may not be significantly improved by an increase in the spatial resolution of the model. |
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| Keywords: | GRAEPS_MESO Time-step size Spatial resolution Model prediction |
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