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An analysis of long‐term relationships among count statistics and metrics of synthetic tropical cyclones downscaled from CMIP5 models
Author(s) -
Reed Andra J.,
Mann Michael E.,
Emanuel Kerry A.,
Titley David W.
Publication year - 2015
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2015jd023357
Subject(s) - tropical cyclone , climatology , atlantic hurricane , storm , structural basin , environmental science , coupled model intercomparison project , sea surface temperature , tropical cyclone rainfall forecasting , tropical cyclone scales , cyclone (programming language) , tropical cyclogenesis , landfall , climate model , climate change , meteorology , geography , geology , oceanography , computer science , field programmable gate array , computer hardware , paleontology
In a changing climate, the impact of tropical cyclones on the United States Atlantic and Gulf Coasts will be affected both by how intense and how frequent these storms become. The observational record of tropical cyclones in the Atlantic Basin is too short (A.D. 1851 to present) to allow for accurate assessment of low‐frequency variability in storm activity. In order to overcome the limitations of the short observational record, we downscale four Coupled Model Intercomparison Project Phase 5 models to generate synthetic tropical cyclone data sets for the Atlantic Basin that span the interval of A.D. 850–2005. Using these long‐term synthetic tropical cyclone data sets, we investigate the relationship between power dissipation and ocean temperature metrics, as well as the relationship between basin‐wide and landfalling tropical cyclone count statistics over the past millennium. Contrary to previous studies, we find only a very weak relationship between power dissipation and main development region sea surface temperature in the Atlantic Basin. Consistent with previous studies, we find that basin‐wide and landfalling tropical cyclone counts are significantly correlated with one another, lending further support for the use of paleohurricane landfall records to infer long‐term basin‐wide tropical cyclone trends.