INVESTIGATING CLIMATIC DRIVERS OF THE WARMING HOLE THROUGH EMPIRICAL DOWNSCALING OF EASTERN U.S. SUMMERTIME MAXIMUM TEMPERATURES

Author

Audrey Wagner, Southern Illinois University CarbondaleFollow

Date of Award

8-1-2011

Degree Name

Master of Science

Department

Geography and Environmental Resources

First Advisor

Schoof, Justin

Abstract

Global average temperatures have increased over the past century, but not all regions of the world have experienced warming. The central United States has experienced less warming than western and eastern portions of the country, with some stations experiencing cooling trends during the period of 1948-2009, leading researchers to dub the area a "warming hole." The causes of this anomaly have been investigated via general circulation models (GCMs) and regional climate model downscaling of GCM output, but conclusions have been limited. This research identifies important drivers of June, July, and August (JJA) mean maximum daily temperature (Tmax) in the region which includes the "warming hole" by developing a model for Tmax using empirical downscaling of large scale variables and local precipitation. First, robust trend analysis is used to determine temperature trends across the country for two time periods: 1948-2009, and 1978-2009; and to locate stations which have experienced cooling, or minimal warming. Second, 19 surface and upper air variables are investigated to identify the optimal independent predictors of Tmax. Station-by-station models of Tmax are produced from National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis sea level pressure, 500 mb geopotential heights, total (meridional and zonal) 850 mb winds in the area of frequent LLJs, as well as station precipitation and assessed for quality. Measures of skill include analysis of error and variance in the modeled time series, as well values of beta-weighted regression coefficients. Third, trends from the modeled time series are calculated and compared with the observed trends. The models show that 500 mb heights have a strong positive correlation with Tmax across the study area, while precipitation widely and uniformly correlates with lower Tmax. Sea level pressure has a negative correlation with Tmax in much of the study area. The LLJ predictor provides novel insight into the climatic drivers in the vicinity of the warming hole, indicating that moisture advection driving nocturnal precipitation plays a role in depressing Tmax.