My research into the remote sensing of cloud-surface coupling and its process-level mechanisms sets a critical foundation for assessing these dynamics within climate models. Our ultimate aim is to refine the representation of these integrated surface-PBL-cloud interactions in multiscale models, from large-eddy simulations and kilometer-scale storm-resolving models to conventional lower-resolution climate models. By achieving this, we improve our capability to accurately simulate the Earth's climate system, thereby deepening our comprehension of how convective systems evolve in response to climate change.

Initiating our research, we delved into cloud-surface coupling within reanalysis data, focusing particularly on the Southern Great Plains. Our detailed investigations revealed the different interactions between various cloud formations, from cumulus to stratiform, and land surface fluxes. This study highlighted deficiencies in current weather forecasting models and reanalysis datasets, such as MERRA-2 and ERA-5, especially their inability to capture the initiation of local convections. These findings emphasize the need for better parameterization for the surface-PBL-cloud coupling processes.

Related Papers:

• Su, T. et al. Observation and Reanalysis Derived Relationships Between Cloud and Land Surface Fluxes Across Cumulus and Stratiform Coupling Over the Southern Great Plains. Geophysical Research Letters. [LINK]

• Su, T. et al. Boundary-Layer-Coupled and Decoupled Clouds in Global Storm-Revolving Models: Comparisons with Field Observations. Upon Submission to JGR: Atmospheres