摘要:使用1980～2017年共38年崇明站逐日降水资料对崇明站年降水量及暴雨日数的特征进行分析，并使用中尺度数值预报模式WRF3.9.1.1（Weather Research and Forecasting model）针对崇明年降水量及暴雨日数异常年份2015年的最强降水过程进行数值模拟，结合站点降水观测资料使用统计方法来系统验证模拟结果。通过敏感性试验着重研究尺度自适应的GF（Grell–Freitas）与传统的KF（Kain–Fritsch）、BMJ（Betts–Miller–Janji?）积云对流参数化方案在不同比率的网格嵌套方式下对于本次过程极端降水总量及逐时变化预报的影响。研究结果表明：使用大比率（9:1或15:1）的双层嵌套可以更真实地模拟强降水区累积降水量分布和逐时变化情况，而使用传统的小比率（3:1或5:1）三层嵌套网格会导致大暴雨和特大暴雨的TS（Threat Score）评分降低，小时降水峰值模拟偏弱等问题；模式外圈使用传统的KF、BMJ积云对流方案比尺度自适应的GF方案对于内圈高分辨率的极端降水总量、逐时变化模拟更有优势，特别是使用KF方案，可以更真实地模拟出极端降水中心的日变化强度；而使用GF方案对于入海口降水模拟偏弱，大暴雨和特大暴雨的TS评分普遍偏低，小时降水峰值也被严重低估。
关键词:WRF模式/
极端降水/
嵌套网格/
积云对流参数化方案
Abstract:This study utilized the observational precipitation data from 1980 to 2017 to analyze the characteristics of annual precipitation and heavy rainfall days at the Chongming station. One extreme heavy rainfall event in 2015 was completely examined using the Weather Research and Forecasting model (version 3.9.1.1) focusing on the impacts of different cumulus parameterization schemes (two traditional schemes, KF and BMJ, and a scale-aware GF scheme) and multigrid nesting configurations. Various statistical methods were adopted to verify the model simulations against the observations. Results showed that using double nesting with a high ratio (9:1 or 15:1) can more realistically produce extreme rainfall distributions and hourly variations compared with the traditional small ratio (3:1 or 5:1) triple nesting grids that produced a lower threat score (TS) for extreme rainfall and underestimated the primary rainfall peaks. On the other hand, the KF and BMJ schemes in the outer grids showed advantages over the GF scheme for the inner 1-km and 3-km simulations of extreme rainfall distribution and hourly rainfall variations. The GF scheme tended to underestimate the extreme rainfall amount over the eastern estuary and TS scores for heavy and extremely heavy rain intensity.
Key words:WRF model/
Extreme heavy rainfall/
Multi-grid nesting/
Cumulus parameterization
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