Collaborative Research: Combining Self-organized Maps and Idealized Storm-scale Simulations to Investigate the Effect of Future Climate Change on Severe Convective Storms

点击翻译按钮获取中文摘要

Severe thunderstorms and tornadoes cause significant damage and loss of life each year worldwide. It remains unclear whether future climate change will make this type of extreme weather worse. This project applies a new methodology to examine how severe thunderstorms and tornadoes may change in a future, warmer climate. This topic is difficult because climate change is a global phenomenon, yet thunderstorms are small – typically less than a few miles in diameter. Different types of computer models can be used to understand future climate change (climate models) and to simulate thunderstorms (storm models). However, one model cannot do both at the same time because of limits on computer power. To overcome this barrier, this project first uses data-based methods to examine how the environments that typically generate severe thunderstorms may change in climate model simulations. The effect of these changes on severe thunderstorms and tornadoes is then tested in simulations using a storm model. The results of both steps can be combined together to examine how severe thunderstorms may change in the future, which will help society better plan and adapt. Recent research suggests that future climate change may enhance the frequency and/or severity of severe convective storms (SCS), including severe thunderstorms and tornadoes. However, studies to date have focused principally on the large-scale environments favorable for SCS activity while neglecting potential changes in storm-scale dynamics. This project integrates climate models, machine learning, and idealized storm-scale ensemble simulations to understand how SCS activity may change in a future warmer climate. This is the first effort to examine future changes in SCS activity by simultaneously accounting for both changes in large-scale environments and storm-scale dynamics. The project has three objectives: 1. Use self-organized maps to quantify changes in structure and variability in SCS soundings in a future warmer climate; 2. Use idealized storm-scale simulations to examine how these changes in SCS soundings will alter probabilities of SCS activity and hazards; 3. Combine results to investigate how SCS activity and hazards may shift geographically and seasonally in a future warmer climate, and understand the underlying environmental vs. storm-scale drivers. This novel approach greatly reduces the high complexity of this problem at both large and small scales across climate states. The outcomes of the project will be compared to prior approaches to this problem to yield a more comprehensive understanding of how SCS activity may change in a future warmer climate.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.