基于MOAT方法的云微物理过程相关参数敏感性评估及北方地区层状云云微物理量的集合预报研究

云微物理量的数值模拟是目前模式研究的重点和难点，而微物理过程的各种参数（例如，冰-液相粒子下落速度/密度、凝华增长速率、冰相粒子凇附速率、雪-霰转化率、云-雨转化率、云-雨转化率等等）的不确定性及其之间复杂的非线性相关性是造成模拟结果，特别是云微物理参量的模拟结果具有很大不确定性的主要原因之一。针对此问题，拟利用MOAT（Morris One at A Time）方法在一维云模式框架下采用不同温湿度和垂直速度条件，系统化、定量化的评估目前中尺度模式中较为完备的微物理方案各类参数敏感性。以此为基础，采用典型天气条件下敏感性微物理参数的扰动构建集合预报成员，通过与飞机垂直观测，卫星反演云微物理量数据的对比分析，优化参数及其扰动配置，建立一套由10-20个成员组成的，适合于北方地区层状云微物理量模拟的集合预报系统，以提高中尺度模式对云微物理量的模拟能力。

The numerical simulation of cloud microphysical properties, such as LWC and IWC, is the focus and difficulty in the model research. Due to the uncertainty of various parameters of microphysical processes (e.g. the fall speed and density of ice/liquid phase particles, the growth rate of condensation process, the riming rate of ice phase particles, the snow-graupel conversion rate, the cloud-rain auto conversion rate, etc.) and the complex nonlinear correlation between them, simulation results of cloud microphysical properties still have large uncertainties. To solve this problem, the MOAT (Morris one at a time) method is proposed to systematically and quantitatively assess the sensitivity of various parameters in the microphysics schemes (e.g Morrison 2-moment) in the current mesoscale model under different temperature, humidity, and vertical velocity conditions. Then, the sensitivity parameters under typical weather conditions are ultilized to construct the ensemble forecast members. Through the comparison with the cloud microphysical data retrieved from the satellite and the vertical observation using the aircraft, the parameters, and their disturbance configuration are optimized, and a set of ensemble forecast system consisting of 10-20 members is established, which is suitable for the simulation of the stratiform cloud microphysical properties in northern China. We hope this method will be helpful in improving the abilities of the mesoscale model to simulate cloud microphysics.