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Mesoscale Convective Systems in E3SMv2 with Default and New Cloud Microphysics and Convection Parameterizations

Presentation Date
Wednesday, December 13, 2023 at 2:10pm - Wednesday, December 13, 2023 at 6:30pm
Location
MC - Poster Hall A-C - South
Authors

Author

Abstract

Mesoscale convective systems (MCSs) play an important role in modulating the global hydrological cycle, general circulation, and radiative energy budget. However, due to the uncertainty in cloud microphysics and convection parameterizations, it is challenging for general circulation models (GCMs) to simulate MCSs. The recently released second version of U.S. Department of Energy (DOE) Energy Exascale Earth System Model (E3SMv2) is not expected to accurately simulate MCSs in its standard 1° resolution. Instead, we created a custom higher resolution configuration to evaluate the impact of the improved cloud physics on simulated MCSs in E3SMv2. A set of 5-year 0.25° resolution E3SMv2 atmosphere model (EAMv2) simulations was performed to evaluate the MCS properties. We track MCSs consistently in the model outputs and observations using the PyFLEXTRKR algorithm. In addition, new cloud microphysics and convection parameterizations are being developed for the next version (v3) of E3SM, including a convective cloud microphysics scheme, the Predicted Particle Properties (P3) stratiform cloud microphysics scheme, the multiscale coherent structure parameterization (MCSP), and the cloud base mass flux adjustment treatment. Sensitivity experiments incorporating all new physics features are tested to understand their impact on the simulation of MCS properties. Our preliminary results show that MCS precipitation rate and MCS occurrence simulated in the default 0.25° EAMv2 are underestimated compared to the observations. The impact of the new cloud and convection parameterizations on simulated MCS properties is more encouraging over the Indo-Pacific region than the Contiguous United States (CONUS) region. Our sensitivity test of the MCS definition in the tracking algorithm suggests the importance of including precipitation feature in MCS tracking when evaluating MCSs in climate models.
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Funding Program Area(s)