TOPOGRAPHY-DEPENDENT HORIZONTAL LOCALIZATION SCALE SCHEME IN GRAPES-MESO HYBRID EN-3DVAR ASSIMILATION SYSTEM

被引:0
|
作者
夏宇 [1 ]
陈静 [2 ]
智协飞 [1 ]
庄照荣 [2 ]
陈良吕 [3 ]
王婧卓 [3 ]
机构
[1] Nanjing University of Information Science & Technology
[2] Chinese Academy of Meteorological Sciences
[3] Numerical Weather Prediction Center China Meteorological Administration
基金
中国国家自然科学基金;
关键词
GRAPES-MESO; hybrid En-3DVAR data assimilation; topography-dependent; horizontal localization scales;
D O I
10.16555/j.1006-8775.2019.02.010
中图分类号
P456.7 [数值预报方法];
学科分类号
摘要
Based on the GRAPES-MESO hybrid En-3 DVAR(Ensemble three-dimension hybrid data assimilation for Global/Regional Assimilation and Prediction system) constructed by China Meteorological Administration, a 7-day simulation(from 10 July 2015 to 16 July 2015) is conducted for horizontal localization scales. 48 h forecasts have been designed for each test, and seven different horizontal localization scales of 250, 500, 750, 1000, 1250, 1500 and 1750 km are set. The 7-day simulation results show that the optimal horizontal localization scales over the Tibetan Plateau and the plain area are 1500 km and 1000 km, respectively. As a result, based on the GRAPES-MESO hybrid En-3 DVAR, a topography-dependent horizontal localization scale scheme(hereinafter referred to as GRAPES-MESO hybrid En-3 DVAR-TD-HLS) has been constructed. The data assimilation and forecast experiments have been implemented by GRAPES-MESO hybrid En-3 DVAR, 3 DVAR and GRAPES-MESO hybrid En-3 DVAR-TD-HLS, and then the analysis and forecast field of these three systems are compared. The results show that the analysis field and forecast field within 30 h of GRAPES-MESO hybrid En-3 DVAR-TD-HLS are better than those of the other two data assimilation systems. Particularly in the analysis field, the root mean square error(RMSE) of uind and vind in the entire vertical levels is significantly less than that of the other two systems. The time series of total RMSE indicate, in the 6-30 h forecast range, that the forecast result of En-3 DVAR-TD-HLS is better than that of the other two systems, but the En-3 DVAR and 3 DVAR are equivalent in terms of their forecast skills. The 36-48 h forecasts of three data assimilation systems have similar forecast skill.
引用
收藏
页码:245 / 256
页数:12
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