Monthly Trends in Maxima of Low Temperatures in Georgia, USA

• Activity Number: 469
• Type: Contributed
• Date/Time: Wednesday, August 6, 2014 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics and the Environment
• Author(s): Lynne Seymour*+ and Waleed Navarro
• Companies: University of Georgia and NASS
• Keywords: moving-block subsampling ; time series ; spatial smoothing ; climate change

Abstract

The monthly maxima of daily low temperatures in the state Georgia are investigated using data from 43 stations taken from the Georgia Automated Environmental Network (GAEMN). Bootstrap methods for time series data are used to model the distribution of the maximum of the low temperatures for each month at each station. The mean and standard deviation of each distribution are then used to standardize each station's data to determine trends. Rates of increase and/or decrease along the distributions are presented along with significance levels. To display the results, contour plots of Georgia are created for each month with the use of a weighted head-banging spatial-smoothing analysis to account for the significance of the trends.