Impact of ENSO and Trends on the Distribution of North American Wintertime Daily Temperature

The true impact of climate, both variability and climate change, is felt through extreme events that last for a few days to weeks, such as heat waves or cold snaps. For the most part, climate studies have focused on aspects of seasonal climate predictability in which the quantity of interest is the monthly or seasonal mean (e.g., seasonal mean temperature), but here we focus on understanding the impact of the El Niño/Southern Oscillation (ENSO) and anthropogenic climate change trends on the statistics of daily temperature within a season. We use a quantile regression model that treats the trends and warm and cool ENSO conditions as three separate predictors, allowing for a nuanced look at changes in the probability distribution function of daily temperature. Trends shift the distribution uniformly throughout North America and have little impact on the inter-quartile range (spread) or higher-order moments. In much of the northern half of the continent, only warm ENSO conditions significantly shift the mean, while only cool ENSO conditions have a significant effect on the southeastern US (negative shift) and Alaska (positive shift). El Niño leads to a contraction of the interquartile range throughout most of the continent, while La Niña has little significant impact on this characteristic.