下垫面类型数据对四川一次降水过程影响的模拟研究

Simulation Study on the Impact of Underlying Soil Type Data on a Precipitation Process in Sichuan

摘要: 为了进一步研究下垫面对西南地区暴雨的影响，本文采用非静力中尺度数值模式WRF-ARW (V3.9.1版)，利用WRF自带的MODIS陆面数据和全球30米精细地表覆盖产品(GLC_FCS30-2020)数据，对发生在四川盆地的一次暴雨过程进行数值敏感性试验，通过天气学诊断分析方法，从动力作用和水汽条件等方面分析不同陆面数据对此次降水过程的模拟，结果表明：1) 此次降水过程是在槽前西南气流、西南低涡以及低空急流加强的共同影响下产生的。强降水主要出现在大巴山地区，降水带呈东北–西南走向，降水强中心出现在四川东北部。2) 两个实验均较好地模拟了此次降水过程。两个模拟的结果在降水水平分布上均偏强、偏西，在时间演变上降水量级更强，峰值持续时间也更长。GLC的模拟结果更加接近观测数据，优化了降水模拟。3) 动力场上，GLC数据模拟出了更弱的辐合，导致了更小垂直速度，在动力抬升方面优化了降水模拟。4) 水汽条件上，近地面水汽含量分布与下垫面类型分布有一定的对应关系，在降水区附近，GLC数据集模拟出更少的水汽含量、更弱的水汽通量和水汽通量辐合，减小了模拟的降水量，在水汽条件方面优化了降水模拟。

Abstract: In order to further study the impact of the underlying surface on heavy rainfall in the southwestern region, this paper uses the non-hydrostatic mesoscale numerical model WRF-ARW (version 3.9.1). Using MODIS land surface data provided by WRF and the global 30-meter refined land cover product (GLC_FCS30-2020), a numerical sensitivity experiment was conducted on a heavy rainfall event that occurred in the Sichuan Basin. Through meteorological diagnostic analysis, the simulation of this rainfall process using different land surface data was analyzed from the aspects of dynamic effects and moisture conditions, and the results show that: 1) This precipitation process is caused by the combined influence of the southwest airflow in front of the trough, the southwest vortex, and the strengthening of the low-level jet stream. Heavy precipitation mainly occurs in the Daba Mountain area, with the precipitation belt trending from northeast to southwest, and the center of intense precipitation appears in northeastern Sichuan. 2) Both experiments simulated the precipitation process well. The results of both simulations are stronger and more westward in the distribution of precipitation levels. In terms of time evolution, the precipitation magnitude is stronger and the peak duration is longer. The simulation results of GLC are closer to the observation data and optimize the precipitation simulation. 3) In the dynamic field, the GLC data simulates weaker convergence, resulting in smaller vertical velocity, and optimizes the precipitation simulation in terms of dynamic lift. 4) In terms of water vapor conditions, there is a certain correspondence between the distribution of water vapor content near the surface and the distribution of underlying surface types. Near the precipitation area, the GLC data set simulates less water vapor content, weaker water vapor flux, and water vapor flux. Convergence reduces the amount of simulated precipitation and optimizes the precipitation simulation in terms of water vapor conditions.