局地地形、地表特征对上海暴雨过程影响的研究

The Analysis of the Influence of the Terrain and the Earth's Surface on the Heavy Rainfall in Shanghai

作者在对2001年8月5～6日上海地区一场特大暴雨的诊断分析与数值模拟研究中确知，停滞在上海的热带低压及在其内发生、发展起来的中尺度对流云团是造成此次暴雨的直接天气系统。暴雨过程中，非常规观测资料及高分辨率暴雨数值模拟结果的分析对于揭示热带低压内暴雨中尺度系统的结构及发展演变的时空连续性具有重要作用。但同时也意识到，对于造成暴雨的各尺度系统的发生、发展，特别是造成局地突发性强降水的暴雨中尺度系统，某些物理过程的影响是不可忽视的。这些物理过程或独立影响着暴雨中尺度系统的发展，或相互作用、相互制约，共同影响着暴雨中尺度系统的发展。为此，作者在此次暴雨过程较成功的数值模拟研究基础上，对上海附近山脉地形及上海地区地表状况等可能影响暴雨中尺度系统发展的物理过程进行了模拟试验研究，结果表明，上海及其周边地区局地山脉地形和上海地区的地表分布特征虽不是造成此次局地突发性强暴雨的直接原因，但明显影响着暴雨系统的移动、停滞、发展和加强。上海以西的莫干山、天目山在热带低压东移过程中对于气流具有一定阻挡作用，有利于暖湿气流的聚集及热带低压移速的减慢。但若山脉过高且热带低压移至非平原地带，则来自西南的暖湿气流会受阻而汇集在莫干山至杭州湾一带，这样在相对强的偏西气流作用下，热带低压的移向就会出现变化。另外，上海局地地表城市化特征的加强使得城市近地层空气的暖干特性效应和城区上风方风速辐合，并由此引起暴雨系统内中尺度动力、热力特征出现变化，这值得在局地暴雨强度预报中加以关注。局地城市地表特征是城市暴雨灾害不容忽视的影响因素。

The strong heavy rainfall with precipitation amount of 294 mm/12 h occurred in Shanghai during 5-6 August 2001 and the serious city disaster appeared. To better under standing of the heavy rainfall process and its predictability, the PSU/NCAR mesoscale model （MMS） has been employed to replicate the process. The simulation results show that the heavy rainfall was mainly associated with the mesoscale convective systems developing in the landed tropical cyclone （TC） and the location, strength and duration agree fairly well with the observation although some deficiencies exist. On the basis of success simulation, the physical processes such as the terrain and the earth＇s surface, which could influence the heavy rainfall, are investigated. The analyses indicate that the mesoscale topography and the characteristic of the surface can influence not only the moving, stagnation and development of the landed tropical cyclone but also the location and intensity of the heavy rainfall indirectly. It is suggest that they are possible to enhance rainfall while favorable weather system stagnates and develops in the city. Therefore, the mesoscale topography and the characteristic of the surface in the city should be taken into account in the movement of the landing tropical cyclone and local severe heavy rainfall precipitation prediction, which will improve the prediction of meteorological disasters in urban area.