M-PERC：一种新的基于卫星微波的热带气旋眼壁置换周期诊断模型

IF 3 3区地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Forecasting Pub Date : 2023-05-23 DOI:10.1175/waf-d-22-0178.1

J. Kossin, D. Herndon, A. Wimmers, Xi Guo, E. Blake

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引用次数: 0

摘要

热带气旋（TC）中的眼壁置换周期（ERC）通常与TC风强度的快速变化和TC风场的拓宽有关，这两者都会带来独特的预测挑战。作为美国国家海洋和大气管理局联合飓风试验台项目的一部分，开发了一个新的模型，为ERC的发生提供操作概率指导。该模型基于TC风强度的时间演变和被动卫星微波图像，并因基于微波的眼壁置换周期概率而命名为“M-PERC”。该模型最初在大西洋盆地开发，但被发现在全球范围内适用且技术娴熟。本文介绍了M-PERC的发展及其性能特点，以及一种新的强度预测模型，该模型扩展了先前的工作。这些模型的应用有望有助于减少TC强度预测误差。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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M-PERC: A New Satellite Microwave-Based Model to Diagnose the Onset of Tropical Cyclone Eyewall Replacement Cycles

Eyewall replacement cycles (ERCs) in tropical cyclones (TCs) are generally associated with rapid changes in TC wind intensity and broadening of the TC wind-field, both of which can create unique forecasting challenges. As part of the NOAA Joint Hurricane Testbed Project, a new model was developed to provide operational probabilistic guidance on ERC onset. The model is based on the time evolution of TC wind-intensity and passive satellite microwave imagery, and is named “M-PERC” for Microwave-based Probability of Eyewall Replacement Cycle. The model was initially developed in the Atlantic basin, but is found to be globally applicable and skillful. The development of M-PERC and its performance characteristics are described here, as well as a new intensity prediction model that extends previous work. Application of these models is expected to contribute to a reduction of TC intensity forecast error.

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来源期刊

Weather and Forecasting 地学-气象与大气科学

CiteScore

5.20

自引率

17.20%

发文量

131

审稿时长

6-12 weeks

期刊介绍： Weather and Forecasting (WAF) (ISSN: 0882-8156; eISSN: 1520-0434) publishes research that is relevant to operational forecasting. This includes papers on significant weather events, forecasting techniques, forecast verification, model parameterizations, data assimilation, model ensembles, statistical postprocessing techniques, the transfer of research results to the forecasting community, and the societal use and value of forecasts. The scope of WAF includes research relevant to forecast lead times ranging from short-term “nowcasts” through seasonal time scales out to approximately two years.