| Literature DB >> 25024204 |
Nathan P Arnold1, Mark Branson2, Melissa A Burt2, Dorian S Abbot3, Zhiming Kuang4, David A Randall5, Eli Tziperman6.
Abstract
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.Entities:
Keywords: climate projections; climate sensitivity; global warming
Mesh:
Substances:
Year: 2014 PMID: 25024204 PMCID: PMC4121830 DOI: 10.1073/pnas.1407175111
Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN: 0027-8424 Impact factor: 11.205