平缓下垫面稳定边界层数值模拟研究

The NWP (numerical weather model) models products which relate to the Planetary Boundary Layer have been focused more and more. However, their performances are restricted by the cold error of near-surface temperature in the stable boundary layer. In this project, high resolution vegetation type data and station observation will be managed to get effective roughness length for NWP model. Then, several single column model experiments will be constructed based on observation experiments over different type surface in the stable boundary layer. The land (sea) - air interaction (including the vertical resolution and first model level sensitive test), two stability parameters (Monin-Obkhov and gradient Richardson number) and several stability functions of K-closure used by modern NWP centers will be evaluated with these SCM experiments. It is expected to elaborately analyze the sources of the stable boundary layer simulation errors over gentle surfaces and find the optimal method to improve the stable boundary layer performance ultimately.

与边界层相关的数值天气预报产品越来越被关注。然而，稳定边界层的模拟误差（如陆地夜间近地面空气温度偏冷）制约模式性能的提高。本研究将使用高分辨率的植被类型资料和台站观测资料为模式推出更合理的有效粗糙度。然后，根据各种下垫面类型的稳定边界层观测试验在单柱模式中构造出多个检验稳定边界层模拟的试验。利用这些试验，通过仔细研究影响平缓下垫面稳定边界层模拟的误差来源: 陆（海）-气相互作用（包括垂直分层加密和模式最低层的选取），1阶K闭合方案常用的两个稳定参数（Monin-Obkhov长度和梯度Richardson数）和多个稳定函数的性能，找到各种影响因素的最优组合，最终改进稳定边界层和数值天气预报模式的模拟性能。