复杂地形下地面观测资料同化I. 模式地形与观测站地形高度差异对地面资料同化的影响研究

中国地形复杂，模式地形与实际观测地形存在一定高度差异，因此设计合理的复杂地形下地面观测资料的同化方案有利于使我国目前仅用作探测手段的地面观测资料（常规地面观测站和地面自动站）在中尺度数值模式中得到充分利用。作者在MM5_3DVAR同化系统中利用近地层相似理论将地面观测资料进行直接三维变分同化分析，并对地面资料同化方案设计中是否需要考虑模式与实际观测站地形高度差异进行探讨研究。研究结果表明：通过近地层相似理论将地面观测资料同化到数值模式能起到一定的作用，并且地面观测资料（温度、 湿度、 风场、 地面气压）中各物理量同化到数值模式都能影响24小时降水数值结果，但各物理量起的作用大小不一样，其中影响最大的是温度，其次为湿度；地面观测资料同化方案设计有必要考虑模式地形与实际观测站地形高度差异，适当考虑这种高度差异能取得较好的结果。

A Study of Assimilation of Surface Observational Data in Complex Terrain Part I: Influence of the Elevation Difference Between Model Surface and Observation Site

Since the topography distribution of China is very complex, there exists elevation difference between surface observation station measurement and numerical model surface. The surface observation data are currently only used as backup or process analysis, but not used in numerical models sufficiently. Reasonable assimilation schemes of surface observation data will put these data into numerical models sufficiently. In this paper, surface observation data are assimilated into Meso-scale model MM5 based on the similarity theory, using MM5_3DVAR (MM5 three-dimensional variational) system. In order to make clear whether the actual elevation difference between observation site and numerical model surface should be put into consideration in directly assimilating surface observation data, some experiments are performed with surface observation data and radiosonde data. Results show that 3DVAR assimilation of surface observation data can impact mesoscale model analysis and forecast. 3DVAR assimilation of each observed surface meteorological parameter can influence the numerical forecast of 24 h rainfall and the effects of different observed surface meteorological parameter assimilation are different. The surface temperature assimilation brings the maximum contribution to the rainfall forecast, followed by the surface moisture. The surface temperature assimilation brings much more contribution to temperature and pressure analysis. The actual difference in elevation between the observation site and the model surface must be put into consideration in the surface observation data assimilation scheme. Better results will be obtained when surface observation data are assimilated into the numerical model where the difference in elevation between observation site and numerical model surface is put into consideration.