Place: 4274 Chamberlin (refreshments will be served)
Speaker: Tristan L'Ecuyer, UW Department of Atmospheric and Oceanic Sciences
Abstract: Simple energy balance arguments indicate that warming from human activities is likely to cause an increase in worldwide precipitation but it is very unlikely that these changes will be felt uniformly around the globe. Climate models indicate, for example, that in a warmer climate “the wet will get wetter and the dry will get drier” – in other words, rainfall is expected to increase in areas that already receive above average rainfall while arid regions may become even drier. Most predictive models also suggest that, as global temperatures rise, the frequency and amount of snowfall in the middle latitudes (where a large fraction of the world’s population resides) will decrease, impacting water availability in areas that depend critically on runoff from winter snow packs. These changes could have significant (and often undesirable) consequences that may require substantial investment to mitigate but developing cost-effective strategies for coping with changing global precipitation patterns must be based on reliable forecasts. Given the transient nature of precipitation, however, evaluating precipitation changes in climate models using the snapshots provided by Earth-observing satellites is a very challenging problem. This presentation will outline a robust statistical method for assessing how long it will take for predicted rain and snowfall trends to emerge from natural year-to-year variations and, therefore, become testable with satellite data records. Utilizing this new strategy, we will reveal a surprisingly robust climate change metric that may be observable by the middle of the next decade.