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Clouds in Climate Models: Identifying Sources of Uncertainty

clouds in the sky

A new study supported by the Climate Program Office’s Modeling, Analysis, Predictions, and Projections (MAPP) Program enhances our understanding of cloud dynamics and how we can improve cloud representation in climate models. Isaac Davis and MAPP-funded researcher Brian Medeira of the National Center for Atmospheric Research assessed cloud behavior in the Community Earth System Model, version 2 (CESM2), a crucial tool for understanding climate change. MAPP supported this project to work toward constraining and understanding climate sensitivity, or the amount of future warming, with process-oriented diagnostics. Brian Medeira also served as a co-lead of MAPP’s Climate Sensitivity Task Force, working to reduce overall uncertainties in future climate projections of phenomena like precipitation, extremes, sea level, sea ice, and more.

Understanding cloud feedback is imperative for reducing uncertainties in climate sensitivity. The research compares model simulations to satellite data to show that while CESM2 generally captures some aspects of real cloud behavior, it struggles to accurately represent certain types of clouds, like those found closer to the Earth’s surface. These low-level clouds are important because they have a big impact on how the climate responds to warming. The results, published in the Journal of Climate, also show that the model fails to characterize the variability of different cloud types in enough detail, leading to larger uncertainties in the final model projections. By understanding how CESM2 simulates clouds and how they change under different climate conditions, scientists can improve the model and make better predictions about future climate change.

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For more information, contact Clara Deck.

Image credit: Pixabay

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