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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Heavy Rain Forecasting by Model Initialization With LAPS: A Case Study
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Heavy Rain Forecasting by Model Initialization With LAPS: A Case Study

机译:通过LAPS模型初始化进行大雨预报:一个案例研究

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摘要

Results of the assimilation of high-density data to initialize the high-resolution meteorological model MOLOCH (CNR-ISAC) are described. The local analysis and prediction system (LAPS), a mesoscale data assimilation system developed at NOAA, is applied to modeling a case study of heavy precipitation that occurred over Liguria, north-western Italy, on November 4, 2011, causing severe flood in the city of Genoa. This case is representative of some episodes that affected the region in the last few years, where the coastal orography, besides enhancing the convective uplift, contributed to the formation of convergence lines over the sea, responsible for the onset of convective cells. The present work aims at the implementation of a model-based operational short-range prediction system, with particular focus on quantitative precipitation forecasting in a time range up to 12–24 h. The use of LAPS analysis as initial condition for the MOLOCH model shows a positive impact on the intensity and distribution of the simulated precipitation with respect to the simulations where only large-scale analyses are employed as initial conditions. Effects on the models simulations are due to the assimilation of surface network data, radio-sounding profiles, radar and satellite (SEVIRI/MSG) data.
机译:描述了对高密度数据进行同化以初始化高分辨率气象模型MOLOCH(CNR-ISAC)的结果。本地分析和预测系统(LAPS)是由NOAA开发的中尺度数据同化系统,用于对2011年11月4日在意大利西北部利古里亚上空发生的强降雨造成严重洪水的案例研究进行建模。热那亚市。该案例代表了最近几年影响该地区的一些事件,沿海地形除了增强对流隆升外,还促进了海上汇聚线的形成,从而导致对流细胞的爆发。目前的工作旨在实施基于模型的业务短程预报系统,特别侧重于在12-24小时内的定量降水预报。与仅将大规模分析用作初始条件的模拟相比,使用LAPS分析作为MOLOCH模型的初始条件显示出对模拟降水强度和分布的积极影响。对模型仿真的影响归因于地面网络数据,无线电声音剖面,雷达和卫星(SEVIRI / MSG)数据的同化。

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