Effects of explicit atmospheric convection at high CO2

The effect of clouds on climate remains the largest uncertainty in climate change predictions, due to the inability of global climate models (GCMs) to resolve essential small-scale cloud and convection processes. We compare preindustrial and quadrupled CO2 simulations between a conventional GCM in w...

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Bibliographic Details
Published in:Proceedings of the National Academy of Sciences
Main Authors: Arnold, Nathan P., Branson, Mark, Burt, Melissa A., Abbot, Dorian S., Kuang, Zhiming, Randall, David A., Tziperman, Eli
Format: Article in Journal/Newspaper
Language:English
Published: National Academy of Sciences 2014
Subjects:
Arctic
Climate change
Sea ice
Online Access:http://nrs.harvard.edu/urn-3:HUL.InstRepos:41384983
https://doi.org/10.1073/pnas.1407175111
Description
Summary:The effect of clouds on climate remains the largest uncertainty in climate change predictions, due to the inability of global climate models (GCMs) to resolve essential small-scale cloud and convection processes. We compare preindustrial and quadrupled CO2 simulations between a conventional GCM in which convection is parameterized and a "superparameterized" model in which convection is explicitly simulated with a cloud-permitting model in each grid cell. We find that the global responses of the two models to increased CO2 are broadly similar: both simulate ice-free Arctic summers, wintertime Arctic convection, and enhanced Madden-Julian oscillation (MJO) activity. Superparameterization produces significant differences at both CO2 levels, including greater Arctic cloud cover, further reduced sea ice area at high CO2, and a stronger increase with CO2 of the MJO. Version of Record

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