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Master's Defense

Department of Atmospheric Science

Fri., Jul. 28, 11:00 am, EN6085

Testing Cloud Microphysics Parameterizations and Improving Representation of Wegner-Bergeron-Findeisen Process in Mixed-phase Clouds in NCAR CAM5

Meng Zhang

University of Wyoming

Abstract

Mixed-phase clouds are persistently observed in the Arctic and the phase partition of cloud liquid and ice in mixed-phase clouds has the important impacts on the surface energy budget and Arctic climate. In this study, we test the NCAR Community Atmosphere Model Version 5 (CAM5) in the single-column and weather forecast modes and evaluate the model performance against the observation data obtained during the DOE Atmospheric Radiation Measurement (ARM) Program’s M-PACE field campaign in October 2004 and long-term ground-based multi-sensor measurements. We find that CAM5, like other global climate models, poorly simulates the phase partition in the mixed-phase clouds by significantly underestimating the cloud liquid water content. An assumption of the pocket structure in the distribution of cloud liquid and ice based on the in situ observation inside the mixed-phase clouds has provided a possible solution to improve the model performance by reducing the Wegner-Bergeron-Findeisen (WBF) process rate. In this study, the modification of WBF process in the CAM5 model has been achieved by applying a random number in the parameters controlling the time scale of WBF relevant to both ice and snow, by assuming the heterogeneous distributions of cloud liquid and ice. Our results show that the modification of WBF process improves the modeled phase partition in the mixed-phase clouds. The seasonality of mixed-phase cloud properties is also better captured in the model when comparing with the long-term ground-based remote sensing observations. Furthermore, the model has little sensitivity to the time step when to update the random number.


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