Collaborative Research: North American Warm-season Extremes in a Changing Climate: Large-scale Drivers and Local Feedbacks

Throughout much of the US climate change will be felt largely through its effects on warm season extreme events like flooding rains, heat waves, fires, and droughts. Basic thermodynamics suggests that the severity and frequency of these events should increase, for instance the hottest heat waves are likely to get hotter in a warming climate and storm intensity is likely to increase because warmer air holds more moisture. The thermodynamic arguments help but the full suite of processes that affect extreme events is extensive and involves a broad range of spatial scales, from the multi-kilometer scale of thunderstorms to the hemispheric scale of the jet streams that drive weather systems. The broad scale range complicates efforts to study extreme event change using weather and climate models, as a brute force effort to simulate all the relevant processes at all the relevant spatial scales, occurring over the decades-long progression of global warming, is not practical even on the largest computers. Climate models can simulate the full global climate system for decades and even centuries but at resolutions too coarse (perhaps 100km grid spacing) to represent the scales of intense storms. In particular they do not capture the mesoscale convective systems (MCSs) which account for much of the severe weather over the continental US. An alternative approach called pseudo-global warming (PGW) uses a high-resolution model to simulate an observed extreme event, and the simulation is repeated with modifications to the ambient conditions to represent the warmer climate. PGW simulations are quite valuable but they only allow consideration of how climate change affects the severity of specific events, thus they do not enable research on changes in the frequency of occurrence of extreme events. Also, PGW simulations are typically conducted using regional models and thus do not properly represent the effects of changes in the hemispheric-scale atmospheric circulation.This project develops a methodology for looking at extreme event change in a warming climate which addresses the multi-scale issue and enables examination of extreme event frequency and other aggregate statistics. First, a high-resolution global model, the Model for Prediction Across Scales (MPAS) is used to simulate the weather and climate of the past 30 years (1990 to 2019). With a grid spacing of 15km the model is capable of representing MCSs. Second, extreme events are identified in this "nature run" and resimulated with modifications to sea surface temperatures and other surface conditions to represent future warming. The modifications are generated using climate model simulations from the Coupled Model Intercomparison Project (CMIP). The resimulations are a form of PGW only with a global domain, so that changes in intensity can be examined accounting for the full range of spatial scales. Third, a set of 30 warm season (May to November) MPAS simulations using CMIP model output is generated to represent future climate change. The warm season simulations follow the PGW approach but the full season duration means that the simulations do not follow particular events but instead show how a typical season of extreme events changes due to warmer conditions. One issue to be addressed with these simulations is the effect of changes in the jet streams over North America on floods and heat waves, as climate models typically show a reduction in jet-level wind speed over the continental US with increases in speed to the north and south.The work is of societal as well as scientific interest given the damaging effects of extreme events and the value of better information on extreme event change to guide decision making. The project also provides support and training to five graduate students and an undergraduate research assistant. Simulations generated in the project are made available to the research community, and reduced versions of the output are hosted on a JupyterHub to provide access to researchers at the universities participating in the project through Jupyter Notebooks. Outreach is conducted through the Junior Curator program North Carolina Museum of Natural Sciences (NCMNS), a program for high school students interested in field biology and conservation. The students collect field mesaurements of local weather events and their impacts, including insect outbreaks, mold, flooding, and other after-effects of heavy rain. Activity guides are created based on these activities and disseminated through the National Association of Geoscience Teachers.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.