Bimodality in Simulated Precipitation Frequency Distributions and Its Relationship with Convective Parameterizations

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Abstract
Bimodality in precipitation frequency distributions is often evident in atmospheric models, but rarely in observations. This study i) proposes a metric to objectively quantify the bimodality in precipitation distributions, ii) evaluates model simulations contributed to the Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5), phase 6 (CMIP6), and the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) project by comparing them to satellite-based and reanalysis precipitation products, and iii) investigates the origin of bimodal precipitation distributions. Our results reveal that about 83% of CMIP5 and 70% of CMIP6 models used in this study exhibit bimodal distributions. The few DYAMOND models that use a deep convective parameterization also show bimodal distributions, while most DYAMOND models do not. Predictably, the bimodality mainly originates from the separation of precipitation process between resolved grid-scale and parameterized subgrid-scale. However, in some models bimodality arises from the parameterized subgrid-scale convective precipitation alone.

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