Society is impacted more by changes in extremes than by changes in averages. By using known methods for assessing climate variability, previously statistically downscaled values of the basic parameters [daily maximum temperature (Tmax), daily minimum temperature (Tmin), and total daily precipitation (Pcpn)], obtained using the Statistical Downscaling Model (SDSM) and the Canadian General Circulation Model 1 (CGCM1) running the Green House Gas + Aerosol 1 (GHG+A1) experiment were re-analyzed. In addition, weather extremes identified using the Statistical and Regional dynamical Downscaling of Extremes for European regions (STARDEX) model were also analyzed for variability.

This study was limited to the analysis of six of the 10 core Stardex annual extremes at one site in Atlantic Canada, namely Greenwood, Nova Scotia. In many, if not all, of the cases examined, increases in either average values (means), variability (standard deviation), or both, indicated substantive increases in their probability of occurrence. In addition, the Extreme Value Analysis (EV1) method of Gumbel projected that by 2100, the return period of the historical (1961-90) 100 year maximum 5-day total precipitation event would recur once every 14 years, a return period reduction by a factor of seven.

According to recently published papers, extensive area specific research conducted in various parts of the world (including western Canada) has concluded that even a slight warming in average surface temperatures in the areas studied increases the likelihood of hail, lightning, tornadoes, heat waves and/or damaging winds. The findings in this paper project significant increases in surface warming at Greenwood Nova Scotia. Until such time as when area specific relationships between increasing temperatures and specific extreme weather events are established, these findings imply that extreme weather events may become more frequent in eastern Canada as well. Furthermore, the projected increases in annual precipitation, falling on significantly fewer days, suggests increasing alternating periods of drought and flood.

These limited findings confirm what most GCM models have long been projecting, i.e. that when downscaled meteorological parameters are projected to increase due to a warmer 2 x CO2 climate (2071-2100), the probability of occurrence of extreme weather increases, sometimes dramatically.