Alleviating Low Cloud Problem in Climate and Weather Forecast Models by Adaptive Vertical Grid Enhancement

Wednesday, December 12, 2018 - 15:25
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The low cloud bias in atmospheric models for climate and weather remains an unsolved problem. Considering the decades of community effort expended on developing and advancing boundary layer and microphysics parameterizations, one realizes just how persistent the low cloud problem is. In this presentation, the primary focus is on the impact of vertical resolution on the representation of low clouds in large scale models. For these models, the effect of vertical resolution on the simulated boundary layer is a relatively unexplored aspect due to limitations in computational resources. We will discuss how low cloud representation is improved by simply increasing vertical resolution in the Energy Exascale Earth System Model (E3SM) and its single column model. Second, we will introduce a new computational method, the Framework for Improvement by Vertical Enhancement (FIVE) coupled with an Adaptive Vertical Grid (AVG). This method will offer better representation of atmospheric boundary layer clouds while limiting additional computational cost due to the increased number of levels. Last, we will discuss a path to E3SM coupled with FIVE-AVG, challenges for developing a computationally efficient FIVE-AVG, and current progress.

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