Using Satellite Observations to Evaluate Model Microphysical Representation of Arctic Mixed-Phase Clouds
Mixed-phase clouds play an important role in determining Arctic warming, but are parametrized in models and difficult to constrain with observations. We use two satellite-derived cloud phase metrics to investigate the vertical structure of Arctic clouds in two global climate models that use the Comm...
| Published in: | Geophysical Research Letters |
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| Main Authors: | , , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10852/97346 https://doi.org/10.1029/2021GL096191 |
| Summary: | Mixed-phase clouds play an important role in determining Arctic warming, but are parametrized in models and difficult to constrain with observations. We use two satellite-derived cloud phase metrics to investigate the vertical structure of Arctic clouds in two global climate models that use the Community Atmosphere Model version 6 (CAM6) atmospheric component. We report a model error limiting ice nucleation, produce a set of Arctic-constrained model runs by adjusting model microphysical variables to match the cloud phase metrics, and evaluate cloud feedbacks for all simulations. Models in this small ensemble uniformly overestimate total cloud fraction in the summer, but have variable representation of cloud fraction and phase in the winter and spring. By relating modeled cloud phase metrics and changes in low-level liquid cloud amount under warming to longwave cloud feedback, we show that mixed-phase processes mediate the Arctic climate by modifying how wintertime and springtime clouds respond to warming. |
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