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Statistical Significance of Trends in the Extremes of Precipitation

PI: R. Saravanan
Institution: Texas A&M University
Additional Investigators: Jerry North, Salil Mahajan
Abstract:
Extreme precipitation events, which often lead to floods or droughts, can significantly disrupt human lives and destroy property. Any systematic change in the frequency of such extreme events could have significant social and economic impacts. Observational studies have suggested that such trends are indeed seen in the occurrence of droughts in certain regions. However, it is difficult to assess the statistical significance of these trends, because nature provides just one realization of the stochastic variability associated with precipitation. In our study, we focus on statistical issues dealing with trends in precipitation. We pursue a two-pronged approach, using two different definitions of extreme events, one based on extreme value statistical theory, and other based on conventional indices such as the Palmer Drought Severity Index. We analyze precipitation variability at nine stations spread across the continental United States. To assess statisical significance, we use a Monte Carlo approach using both observational data and simulated data obtained from coupled and uncoupled GCMs. Thus far we have obtained data from the NCAR CCSM3 and PCM integrations. We would like to extend our analysis to include other models from the IPCC suite of integrations.
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