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The simulation of heavy rainfall episode over Mumbai: impact of horizontal resolutions and cumulus parameterization schemes

机译:孟买暴雨过程的模拟:水平分辨率和积云参数化方案的影响

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摘要

In this study, the simulation of an extreme weather event like heavy rainfall over Mumbai (India) on July 26, 2005 has been attempted with different horizontal resolutions using the Advanced Research Weather Research Forecast model version 2.0.1 developed at the National Center for Atmospheric Research (NCAR), USA. The study uses the Betts–Miller–Janjic (BMJ) and the Grell–Devenyi ensemble (GDE) cumulus parameterization schemes in single and nested domain configurations. The model performance was evaluated by examining the different predicted parameters like upper and lower level circulations, moisture, temperature, and rainfall. The large-scale circulation features, moisture, and temperature were compared with the National Centers for Environmental Prediction analyses. The rainfall prediction was assessed quantitatively by comparing rainfall from the Tropical Rainfall Measuring Mission products and the observed station values reported in the Indian Daily Weather Reports from India Meteorological Department (IMD). The quantitative validation of the simulated rainfall was done by calculating the categorical skill scores like frequency bias, threat scores (TS), and equitable threat scores (ETS). It is found that in all simulations, both in single and nested domains, the GDE scheme has outperformed the BMJ scheme for the simulation of rainfall for this specific event. Keywords Mumbai rainfall - TRMM rainfall - Cumulus parameterization
机译:在本研究中,使用美国国家大气中心开发的高级研究天气研究预测模型版本2.0.1,尝试以不同的水平分辨率模拟2005年7月26日在印度孟买等极端天气事件。研究(NCAR),美国。该研究在单个和嵌套域配置中使用了Betts-Miller-Janjic(BMJ)和Grell-Devenyi合奏(GDE)累积参数化方案。通过检查不同的预测参数(例如上下循环,湿度,温度和降雨)来评估模型性能。将大规模的循环特征,湿度和温度与美国国家环境预测中心进行了比较。通过比较热带降雨测量任务产品的降雨量和印度气象局(IMD)的《印度每日天气报告》中报告的观测站值,对降雨预测进行了定量评估。通过计算分类技能得分(例如频率偏差,威胁得分(TS)和公平威胁得分(ETS))来完成对模拟降雨的定量验证。发现在所有模拟中,无论是在单个域还是嵌套域中,GDE方案都比BMJ方案在此特定事件的降雨模拟方面要好。孟买降雨-TRMM降雨-积云参数化

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