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Tropical cyclones in climate models
Author(s) -
Camargo Suzana J.,
Wing Allison A.
Publication year - 2015
Publication title -
wiley interdisciplinary reviews: climate change
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.678
H-Index - 75
eISSN - 1757-7799
pISSN - 1757-7780
DOI - 10.1002/wcc.373
Subject(s) - downscaling , climate model , climate change , climatology , environmental science , tropical cyclone , scale (ratio) , computer science , meteorology , geography , precipitation , geology , cartography , oceanography
In this review, we provide a historical overview of the simulation of tropical cyclones (TCs) in climate models, from the first attempts in the 1970s to the current state‐of‐the‐art models. We discuss the status of TC simulation across multiple time scales, from intraseasonal, seasonal, and decadal, to climate change. One of the limitations on the simulation of TCs in climate models has been, and continues to be, balancing the high resolution necessary to accurately simulate TCs themselves with the need to run simulations for many years and using many ensemble members. Several approaches to inferring TC activity indirectly, rather than relying on the models own under‐resolved TCs, are reviewed, including the use of TC genesis indices based on the large‐scale environment and downscaling methods such as the use of regional climate models and statistical–dynamical techniques. We also provide an update on the status of climate change projections from the current class of models, where it is feasible to directly track the model's TCs. While there has been great progress in the capability of climate models to simulate TCs and provide useful forecasts and projections across multiple time scales, there remains much work to be done. We list some of the sources of uncertainty and model sensitivity, describe where improvements are necessary, and provide a few suggestions for promising research directions. WIREs Clim Change 2016, 7:211–237. doi: 10.1002/wcc.373 This article is categorized under: Climate Models and Modeling > Knowledge Generation with Models