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Weather Radar Network Benefit Model for Tornadoes

机译:天气雷达网络福利模型龙卷风

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摘要

A monetized tornado benefit model is developed for arbitrary weather radar network configurations. Geospatial regression analyses indicate that improvement of two key radar parameters-fraction of vertical space observed and cross-range horizontal resolution-leads to better tornado warning performance as characterized by tornado detection probability and false-alarm ratio. Previous experimental results showing faster volume scan rates yielding greater warning performance are also incorporated into the model. Enhanced tornado warning performance, in turn, reduces casualty rates. In addition, lower false-alarm ratios save costs by cutting down on work and personal time lost while taking shelter. The model is run on the existing contiguous U.S. weather radar network as well as hypothetical future configurations. Results show that the current radars provide a tornado-based benefit of similar to$490 million (M) yr(-1). The remaining benefit pool is about $260M yr(-1), split roughly evenly between coverage- and rapid-scanning-related gaps.
机译:为任意天气雷达网络配置开发了一种货币化龙卷风福利模型。地理空间回归分析表明,改进了两个关键雷达参数 - 观察到的垂直空间的分数和跨范围水平分辨率 - 导致更好的龙卷风警告性能,其特征在于龙卷风检测概率和假警报比。之前的实验结果显示出更快的体积扫描速率,产生更大的警告性能也纳入了模型中。反过来,增强了龙卷风警告性能降低了伤亡率。此外,较低的假警报比率通过减少工作和个人时间在避难所时减少成本。该模型在现有的连续U.S.天气雷达网络以及假设的未来配置上运行。结果表明,目前的雷达提供了基于龙卷风的益处,类似于4.9亿美元(M)Yr(-1)。剩余的福利池约为260米,覆盖率和快速扫描相关空隙之间大致均匀均匀。

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