Distinct Impacts of Global Warming on Mesoscale Convective Systems and Isolated Deep Convection in the Eastern United States
Convective systems are a vital part of the Earth’s hydrological cycle, atmospheric circulation, and radiation balance. It is thus useful to understand how convective systems may respond to global warming and modulate weather and climate. Recent studies have emphasized more extreme mesoscale convective systems (MCSs), while the smaller but more frequent isolated deep convection (IDC) systems that also play important roles in the Earth system are often overlooked. Using the regionally refined Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) and pseudo global warming (PGW) experiment framework, we investigate the potential impact of global warming on convective storms in the eastern United States, focusing on a 50-day period from July 1 to August 19, 2020. An updated Flexible Object Tracker (FLEXTRKR) algorithm is used to identify MCS and IDC events from the SCREAM simulations. The control simulation (CTRL) with prescribed sea surface temperature and initialized using reanalysis data can reproduce the observed MCS and IDC characteristics well. By comparing the CTRL simulation with the PGW simulation under end-of-century SSP5-8.5 scenario conditions, we find an increase in the number of MCS events but a decrease in IDC events in the future. In addition, the mean MCS lifetime becomes shorter under global warming, while IDC lives longer. Concurrently, the convective cores of both MCS and IDC events become larger and stronger while their stratiform areas shrink. Also importantly, regions with the most frequent MCS and IDC occurrences are found to shift significantly as MCS and IDC tend to occur closer to the southern and eastern coastal areas with higher relative humidity under global warming. As the first study to investigate the impact of global warming on convective systems at different scales, this work unveils the complexity of the responses of convective systems to climate change and motivates further research to understand the underlying mechanisms for various changes of MCS and IDC using cloud-resolving and theoretical models.