使用数值天气预报模式资料的风切变/微暴探测算法在热带气旋个案中的表现

IF 2 4区地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES

Atmospheric Science Letters Pub Date : 2023-05-02 DOI:10.1002/asl.1173

P. W. Chan, K. K. Lai, W. Kong, S. M. Tse

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引用次数: 0

摘要

香港国际机场使用了三种风切变/微暴探测算法。本文通过假设从数值天气预报模式输出的完整气象数据集的可用性来研究它们的性能。只考虑选定的热带气旋情况。使用风切变的飞行员报告来评估性能。结果表明，考虑相对运行特征曲线下面积的滑翔路径扫描风切变检测算法具有最佳的综合性能。这可能与这种特殊算法在覆盖机场下滑路径时更好的几何形状有关。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Performance of windshear/microburst detection algorithms using numerical weather prediction model data for selected tropical cyclone cases

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Performance of windshear/microburst detection algorithms using numerical weather prediction model data for selected tropical cyclone cases

Three windshear/microburst detection algorithms are used operationally at the Hong Kong International Airport. Their performance is studied in the present article by assuming the availability of the complete set of meteorological data from numerical weather prediction model output. Only selected tropical cyclone cases are considered. The performance is evaluated using pilot reports of windshear. It turns out that the glide path scan windshear detection algorithm has the best overall performance by considering the area under curve using the relative operating characteristic curves. This may be related to the better geometry in covering the glide paths of the airport for this particular algorithm.

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来源期刊

Atmospheric Science Letters METEOROLOGY & ATMOSPHERIC SCIENCES-

CiteScore

4.90

自引率

3.30%

发文量

审稿时长

>12 weeks

期刊介绍： Atmospheric Science Letters (ASL) is a wholly Open Access electronic journal. Its aim is to provide a fully peer reviewed publication route for new shorter contributions in the field of atmospheric and closely related sciences. Through its ability to publish shorter contributions more rapidly than conventional journals, ASL offers a framework that promotes new understanding and creates scientific debate - providing a platform for discussing scientific issues and techniques. We encourage the presentation of multi-disciplinary work and contributions that utilise ideas and techniques from parallel areas. We particularly welcome contributions that maximise the visualisation capabilities offered by a purely on-line journal. ASL welcomes papers in the fields of: Dynamical meteorology; Ocean-atmosphere systems; Climate change, variability and impacts; New or improved observations from instrumentation; Hydrometeorology; Numerical weather prediction; Data assimilation and ensemble forecasting; Physical processes of the atmosphere; Land surface-atmosphere systems.