A Quantitative Method to Evaluate Tropical Cyclone Tracks in Climate Models

被引:12
作者
Shen, Yixuan [1 ]
Sun, Yuan [1 ,2 ]
Camargo, Suzana J. [3 ]
Zhong, Zhong [1 ]
机构
[1] Natl Univ Def Technol, Coll Meteorol & Oceanog, Nanchang, Jiangxi, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Joint Int Res Lab Climate & Environm Change ILCEC, Nanchang, Jiangxi, Peoples R China
[3] Columbia Univ, Lamont Doherty Earth Observ, Palisades, NY USA
基金
美国海洋和大气管理局;
关键词
Tropical cyclones; Climate models; WESTERN NORTH PACIFIC; CLUSTER-ANALYSIS; CMIP5; MODELS; TYPHOON TRACKS; FUTURE CHANGES; CIRCULATION; INTENSITY; SIMULATIONS; FREQUENCY; GENESIS;
D O I
10.1175/JTECH-D-18-0056.1
中图分类号
P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
The ability to simulate tropical cyclones (TCs) realistically is an important factor in the performance evaluation of climate models. In previous studies, indirect evaluation methods have been proposed that are based on the comparison of TC-related background circulation between model results and observations. Direct model evaluation methods, in most cases, are limited to the model skill in simulating the TC frequency, intensity, and track density. Here we propose a new method to quantitatively and directly evaluate the ability of climate models in simulating TC tracks. The method consists of two indicators that account for the model performance in simulating TC track density and the geographic properties of TC tracks, respectively. This method is applied to evaluate the skill of climate models in simulating TC tracks over the western North Pacific Ocean. The explicit models include seven from phase 5 of the Coupled Model Intercomparison Project and eight from the U.S. CLIVAR Hurricane Working Group (HWG), as well as four downscaled HWG models. Our results indicate the order of these 15 explicit models according to their ability to simulate TC tracks. In addition, we show that, for one of the models, the TC track simulation is greatly improved by using downscaling.
引用
收藏
页码:1807 / 1818
页数:12
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