Quantifying the climatological environmental influence on tropical cyclone intensity
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Thursday, 8 January 2015
, Florida State University, Tallahassee, FL; and J. Elsner
and T. H. Jagger
As we strive to better understand the relationship between tropical cyclones (TCs) and climate, global climate models (GCMs) have become a valuable tool and resource. However, despite notable progress in physics and resolution, GCMs are still unable to realistically simulate the inner core structure of intense TCs. Given this limitation, we must exercise caution when using GCMs to predict and understand how climate change may affect future TC activity, particularly with respect to intensity. Although climate models do not yet realistically simulate TC intensity and structure, they do a somewhat better job of capturing the large scale environmental fields that influence how intense a TC may become. Therefore, if we can use observational data to understand how various environmental variables (e.g., sea surface temperature, vertical wind shear, mid-level relative humidity) influence the maximum intensity of TCs, we may be able to utilize GCM simulations of relevant environmental variables to infer information about TC intensity in the future. This research thus has two aims: first, to create a spatio-temporal model for observed TC intensity, and second, to use that model to infer future TC intensity by employing environmental data from 21st century GCM simulations.
The work presented here will focus on the first goal. We use observational and reanalysis data from the 1979—2012 period to assess the influence of key environmental variables on TC intensity for the North Atlantic Basin. To accomplish this, we utilize a spatial lattice approach and a Bayesian spatio-temporal statistical model that examines the relationship between regional TC maximum intensity and several environmental variables from the MERRA reanalysis: sea surface temperature, 200—850 hPa wind shear, and 400—700 hPa relative humidity. The model also considers El Niño/Southern Oscillation effects by incorporating a term for the Southern Oscillation Index (SOI). Results from this portion of the study allow us to quantify the spatially and temporally varying influence of relevant environmental variables on TC intensity. Overall, SST has the largest fixed effect relative to shear, relative humidity, and SOI.