The Climatic Impacts of a Satellite‐Based Parameterization of the Wegener‐Bergeron‐Findeisen Process for Large‐Scale Models

Abstract A satellite‐based temperature‐dependent parameterization of the Wegener‐Bergeron‐Findeisen (WBF) process that takes into account the subgrid‐scale variability of cloud thermodynamic phase within mixed‐phase clouds is developed and implemented in version 5.3 of the Community Atmosphere Model (CAM5.3). Its impact on cloud microphysical and macrophysical properties in experiments with prescribed sea surface temperature and sea ice concentrations as well as the cloud feedback response to a global warming perturbation is investigated. The parameterization significantly improves overestimates in the mass of ice within mixed‐phase clouds and ice effective radius relative to satellite observations, the former being superior to tuning the WBF process with a multiplicative constant. The parameterization also reduces overall biases in cloud fraction with respect to satellite observations, however, is due to compensating biases in existing simulated low biases in low‐level cloud cover and new increased biases in non‐low‐level cloud cover. The increased bias in non‐low‐level cloud cover is due to decreases in the rate of autoconversion of cloud ice that is a side effect of the WBF parameterization. While the WBF parameterization can significantly impact the magnitude of model biases in cloud properties and the cloud feedback, it does not significantly change their spatial distribution. Before observational constraints on WBF process rates become available, it is recommended that temperature‐dependent scalings of the WBF process are used to account for the subgrid‐scale variability of cloud phase rather than a constant scaling parameter as the former type of parameterization can more realistically simulate cloud properties relative to satellite observations.