CAREER: Understanding Changes in Summertime Continental Temperature Extremes

University Of California-Los Angeles, Los Angeles CA

Investigators

Abstract

Heat waves of unprecedented intensity and duration are expected in a warming world, and the record-breaking heat waves of recent years confirm this expectation. The increasing frequency of such events is alarming and naturally leads to concerns that the severity of heat waves is outpacing the rise in mean temperature. But the extent to which the hottest days are warming faster than the average temperature increase is hard to quantify, and certainly heat waves would become more severe even if the hottest days warmed at the same rate as all the other days. One challenge is that heat extremes are rare by definition, thus there is limited sample size to make statistically robust conclusions. The sample size issue is particularly challenging as the extent to which the hottest days warm faster is likely to vary from one region to another. A further challenge is that we do not have a satisfactory understanding of the physical mechanisms that might lead to stronger warming trends for hot days than for average days. Work under this award addresses both the extent to which temperature increases are greater for the hottest days and the physical mechanisms the might be responsible. The analysis of temperature trends compares trends for the 50th and 95th percentiles of the temperature distribution on a regional basis and uses various statistical methods to overcome sample size limitations and account for natural variability. The analysis also considers output from the simulations available from the Climate Model Intercomparison Project (CMIP) and the Large Ensembles created with the Community Earth System Model (CESM). Work addressing physical mechanisms focuses the extent to which drying of the soil contributes to temperature extremes, in particular that drying accompanies heat waves and drying limits the extent to which the surface can cool through evaporation and transpiration, thus leading to greater warming. The dependence of temperature extremes on soil moisture and evapotranspiration is explored by applying a surface energy budget equation to observations and model output, and through idealized experiments with CESM. The educational component of this CAREER proposal seeks to build a bridge between climate and data science to foster more effective collaboration between the two fields. One activity is the development of an educational module for a freshman class in environmental science intended to teach statistical thinking through hands-on data analysis. The module uses Juypiter notebooks to give students access to observational data for their own hometowns, and guides them through the calculation of means and extremes and their variation over time. Another activity is a workshop for 30-40 graduate students working at the interface between data science and climate science, to be held at the National Center for Atmospheric Research (NCAR). The workshop is mostly devoted to a 'science hackathon' in which teams of students with a mix of disciplinary backgrounds will work together to solve specific problems related to climate extremes. The award provides support for 20 attendees at the workshop who are chosen through an open competitive process. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.