Evaluation of Downscaled CMIP5 Model Skill in Simulating Daily Maximum Temperature Over the Southeastern United States

Abstract:

Downscaled CMIP5 climate projections of maximum daily temperature from the Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections archive are examined regionally over the southeastern U.S. Three measures of model skill (means-based, distribution-based, extreme-based) are utilized to assess the ability of 15 downscaled models to simulate daily maximum temperature observations. A new test is proposed to determine statistical significance of the probability density function based skill measures. Skill scores are found to be generally high for all three measures throughout the study region, but lower scores are present in coastal and mountainous areas. Application of the significance test shows that while the skill scores may be high they are not significantly higher than could be expected at random in some areas. The distribution-based skill scores are not significant in much of Florida and the Appalachians. The extreme-based skill scores are not significant in more than 90% of the region for all models investigated. The findings suggest that although the downscaled models have simulated observed means well and are a good match to the entire distribution of observations, they are not simulating the occurrence of extreme (above 90^th percentile) maximum daily temperatures.