DOE Early Career Award # DE-SC0012152: Understanding the Roles of Cloud Microphysics and Land Surface Coupling Feedbacks in Multi-Scale Predictions of Central US Summer Hydroclimate (Final Report)
This summarizes technical highlights from the DOE Early Career Project entitled “Understanding the Roles of Cloud Microphysics and Land Surface Coupling Feedbacks in Multi-Scale Predictions of Central US Summer Hydroclimate” led by PI Mike Pritchard at the University of California. The project’s original aims were to investigate trade-offs of cloud superparameterization such as the effects of microphysical assumptions on mesoscale convective systems (Section I) and the representation of land-atmosphere coupling under explicit convection (Section II). Under the same broader theme of water cycle dynamics, superparameterization, and land interaction, the project evolved to further investigate the climate dynamics of irrigation, vegetation and streamflow (Section III), the dynamics of the Madden- Julian Oscillation (Section IV), as well as the use of modern machine learning to replace traditional sub grid approaches for climate simulation (Section V). Twenty peer-reviewed journal publications were produced as a result of this project (Section VI).