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Cluster Analysis of Downscaled and Explicitly Simulated North Atlantic Tropical Cyclone Tracks

Cited 46 time in Web of Science Cited 47 time in Scopus
Authors

Daloz, Anne S.; Camargo, S. J.; Kossin, J. P.; Emanuel, K.; Horn, M.; Jonas, J. A.; Kim, D.; LaRow, T.; Lim, Y. -K.; Patricola, C. M.; Roberts, M.; Scoccimarro, E.; Shaevitz, D.; Vidale, P. L.; Wang, H.; Wehner, M.; Zhao, M.

Issue Date
2015-02
Publisher
American Meteorological Society
Citation
Journal of Climate, Vol.28 No.4, pp.1333-1361
Abstract
A realistic representation of the North Atlantic tropical cyclone tracks is crucial as it allows, for example, explaining potential changes in U.S. landfalling systems. Here, the authors present a tentative study that examines the ability of recent climate models to represent North Atlantic tropical cyclone tracks. Tracks from two types of climate models are evaluated: explicit tracks are obtained from tropical cyclones simulated in regional or global climate models with moderate to high horizontal resolution (1 degrees-0.25 degrees), and downscaled tracks are obtained using a downscaling technique with large-scale environmental fields from a subset of these models. For both configurations, tracks are objectively separated into four groups using a cluster technique, leading to a zonal and a meridional separation of the tracks. The meridional separation largely captures the separation between deep tropical and subtropical, hybrid or baroclinic cyclones, while the zonal separation segregates Gulf of Mexico and Cape Verde storms. The properties of the tracks' seasonality, intensity, and power dissipation index in each cluster are documented for both configurations. The authors' results show that, except for the seasonality, the downscaled tracks better capture the observed characteristics of the clusters. The authors also use three different idealized scenarios to examine the possible future changes of tropical cyclone tracks under 1) warming sea surface temperature, 2) increasing carbon dioxide, and 3) a combination of the two. The response to each scenario is highly variable depending on the simulation considered. Finally, the authors examine the role of each cluster in these future changes and find no preponderant contribution of any single cluster over the others.
ISSN
0894-8755
URI
https://hdl.handle.net/10371/200996
DOI
https://doi.org/10.1175/JCLI-D-13-00646.1
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  • College of Natural Sciences
  • Department of Earth and Environmental Sciences
Research Area Climate Change, Earth & Environmental Data, Severe Weather, 기후과학, 위험기상, 지구환경 데이터과학

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