Statistical Characterization of Relationships Between Precipitation Extremes and Atmospheric Covariates

• Activity Number: 24
• Type: Topic Contributed
• Date/Time: Sunday, July 29, 2012 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Evan Kodra*+ and Snigdhansu Chatterjee and Auroop R Ganguly
• Companies: Northeastern University and University of Minnesota and Northeastern University
• Keywords: precipitation ; extremes ; climate ; uncertainty ; evaluation ; regression

Abstract

Projections of precipitation remain among the most uncertain among climate model variables. The extremes of precipitation, which may be more directly relevant to various impacts sectors, are known to have a dependence on temperature, which in turn is better projected from models than precipitation. One question that has been explored in the literature is whether the temperature dependence can be used to enhance projections of precipitation extremes beyond what is directly derived as climate model simulations. The Clausius Clapeyron relation provides a physics-based equation between the temperature and the saturation water vapor pressure of the atmospheric column and hence potentially to rainfall extremes. Depending on the proportion of extreme precipitation produced by convective versus large-scale effects, the role of covariates other than temperature, such as upward velocity in the atmospheric column or relative humidity profiles, may become more or less important. We attempt to characterize the extremes with a statistical model that incorporates atmospheric covariates and allows for spatio-temporal autocorrelation effects.