Remote forcings on summertime heat waves across the United States

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Monday, 3 February 2014: 4:00 PM
Room C102 (The Georgia World Congress Center )
Tiffany T. Smith, Johns Hopkins Univ., Baltimore, MD; and B. F. Zaitchik and S. D. Guikema

Increasing mean global temperatures along with recent deadly heat wave events (Europe, 2003; Russia 2010; United States, 2012) have brought attention to the frequency, intensity and consequences of extreme high temperatures. Accordingly, researchers have begun to specifically consider the influence of global climate modes on extreme heat events. Most studies, however, have focused on a single region or climate mode, and in the continental United States (CONUS) the winter has been more studied than the summer. Here, we conduct a comprehensive analysis of the impact global climate modes have on summertime heat wave events across CONUS. Our previous research has shown that regional patterns and temporal trends in heat waves are definition-specific. Therefore, we have used data from the North American Land Data Assimilation System (NLDAS-2) to create monthly counts of heat waves days, as defined by four different heat wave definitions. Multiple global climate modes, such as El Nino Southern Oscillation (ENSO), North American Oscillation (NAO), Pacific Decadal Oscillation (PDO) etc., have been assessed across seven CONUS regions over the 1980-2012 time period. In addition, multiple statistical modeling techniques are utilized to best capture the effects of these climate modes on heat waves. Preliminary results suggest that the influence of large-scale climate modes differs by heat wave definition and CONUS region. For example, using a heat wave definition based on the 90th percentile of mean daily temperature, the Southeast (SE) saw ENSO and NAO as the most important variables while the Southern Great Plains (SGP) saw PDO and NAO as the most important variables. When using a heat wave definition based on maximum daily temperature over 35C, the most important variables didn't change for the SE, however the SGP saw ENSO and PDO as the most important variables. These differences are highly relevant to seasonal forecasts of extreme heat events and to projections of climate change impacts across heat-vulnerable regions of CONUS.