Statistical analysis of factors affecting the genesis of tropical Atlantic cyclones in climate model simulations
R. Saravanan, Texas A&M University, College Station, TX; and S. Mahajan
Tropical cyclone genesis is affected by several large-scale environmental factors, such as the vertical wind shear, relative humidity, etc. It is therefore very important to understand how these factors are affected by climate variations, both natural and anthropogenic. Recently, the issue of trends in the intensity of tropical cyclones has been a subject of great controversy. However, the related issue of variations in tropical cyclone frequency has received somewhat less attention. This is in part because there is no clear statistical trend in the observed global cyclone frequencies. Since the trend signal is weak, it requires more extensive statistical analysis of observations to isolate it. As observational data are limited, it would be useful to extend the analysis to data from climate model simulations.
Although coarse-resolution climate models cannot be used to study the actual genesis of tropical cyclones, they can be used to investigate the trends in environmental factors. In this study, we perform a statistical analysis of the ensemble of climate model simulations carried out for the Intergovernmental Panel on Climate Change (IPCC) 4th Assessment. These simulations are available from the PCMDI data archive. We consider both model simulations of the 20th century and model projections for the 21st century. Multivariate analysis is used to identify statistically robust indicators of tropical cyclone genesis for the 20th century simulations, by comparing the simulated large-scale environmental factors to observed cyclone frequencies. The focus is on the Main Development Region for tropical cyclones in the Atlantic, but the remote influence of phenomena such as the El Nino-Southern Oscillation (ENSO) and West African rainfall are also explicitly considered. The robust indicators identified by the statistical analysis are then used to identify secular trends for the 21st century projections that are consistent across different models.
Session 7, Climate and Extreme Weather Events I
Thursday, 18 January 2007, 1:30 PM-5:30 PM, 214B
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