Seminar - Toward a Process-Based Understanding of the Shallow Cumulus Cloud Life Cycle
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A major challenge in weather and climate prediction is the limited understanding of the processes governing the life cycle of shallow cumulus clouds. We investigate three key aspects of shallow cumulus evolution: cloud initiation, cloud–cloud interactions, and cloud microphysical evolution. Using radiosonde observations, MODIS satellite retrievals, and large-eddy simulations (LES), we show that topography primarily controls where shallow cumulus clouds initiate through orographic circulations, while soil moisture regulates cloud amount by modulating surface sensible heat fluxes. Realistic and idealized LES further reveal that neighboring clouds compete for available energy and moisture, with growing clouds suppressing the development of nearby clouds; the strength of this competition depends on cloud spacing and surface forcing. Finally, LES combined with a minimal theoretical model demonstrates a non-monotonic relationship between cloud droplet spectral relative dispersion and aerosol number concentration, resulting from the competing effects of turbulence-induced spectral broadening and condensational narrowing. Together, these studies provide a process-based understanding of how land surface heterogeneity, cloud interactions, and aerosol–cloud microphysics jointly regulate the evolution of shallow cumulus clouds, offering physical insights for improving cloud parameterizations in weather and climate models.
Prof. Jingyi Chen is currently a professor at Nanjing University of Information Science and Technology. She obtained her bachelor's degree from Peking University in 2011 and her Ph.D. from the State University of New York at Stony Brook in 2018. Following this, she worked as a postdoctoral researcher and then as a scientist at the Pacific Northwest National Laboratory from 2018 to 2024. Her research focuses on addressing several significant challenges related to cloud processes at the sub-grid scale. These challenges include the formation and upscale growth of shallow clouds, the interactions between land, the atmospheric boundary layer, and clouds, as well as the interactions between aerosols and clouds. These processes at the sub-grid level are often simplified within Earth System Models (ESMs) due to their finer spatial and temporal scales, which necessitate parameterization, and a lack of clear theoretical understanding. Understanding and accurately parameterizing these sub-grid cloud processes will lead to improved predictions of the Earth’s energy and hydrological cycles.