Clouds and Convective Self-Aggregation in a Multimodel Ensemble of Radiative-Convective Equilibrium Simulations.
Allison A Wing, Catherine L Stauffer, Tobias Becker, Kevin A Reed, Min-Seop Ahn, Nathan P Arnold, Sandrine Bony, Mark Branson, George H Bryan, Jean-Pierre Chaboureau, Stephan R De Roode, Kulkarni Gayatri, Cathy Hohenegger, I-Kuan Hu, Fredrik Jansson, Todd R Jones, Marat Khairoutdinov, Daehyun Kim, Zane K Martin, Shuhei Matsugishi, Brian Medeiros, Hiroaki Miura, Yumin Moon, Sebastian K Müller, Tomoki Ohno, Max Popp, Thara Prabhakaran, David Randall, Rosimar Rios-Berrios, Nicolas Rochetin, Romain Roehrig, David M Romps, James H Ruppert, Masaki Satoh, Levi G Silvers, Martin S Singh, Bjorn Stevens, Lorenzo Tomassini, Chiel C van Heerwaarden, Shuguang Wang, Ming Zhao
Author Information
Allison A Wing: Department of Earth, Ocean and Atmospheric Science Florida State University Tallahassee FL USA. ORCID
Catherine L Stauffer: Department of Earth, Ocean and Atmospheric Science Florida State University Tallahassee FL USA. ORCID
Tobias Becker: Max Planck Institute for Meteorology Hamburg Germany. ORCID
Kevin A Reed: School of Marine and Atmospheric Sciences Stony Brook University Stony Brook NY USA. ORCID
Min-Seop Ahn: Department of Atmospheric Sciences University of Washington Seattle WA USA. ORCID
Nathan P Arnold: Global Modeling and Assimilation Office NASA Goddard Space Flight Center Greenbelt MD USA. ORCID
Sandrine Bony: Laboratoire de Météorologie Dynamique (LMD)/IPSL/Sorbonne Université/CNRS Paris France. ORCID
Mark Branson: Department of Atmospheric Science Colorado State University Fort Collins CO USA. ORCID
George H Bryan: National Center for Atmospheric Research Boulder CO USA. ORCID
Jean-Pierre Chaboureau: Laboratoire d'Aérologie, Université de Toulouse, CNRS, UPS Toulouse France. ORCID
Stephan R De Roode: Faculty of Civil Engineering and Geosciences, Department of Geoscience and Remote Sensing Delft University of Technology Delft Netherlands. ORCID
Kulkarni Gayatri: Indian Institute of Tropical Meteorology Pune India. ORCID
Cathy Hohenegger: Max Planck Institute for Meteorology Hamburg Germany. ORCID
I-Kuan Hu: Rosenstiel School of Marine and Atmospheric Science University of Miami Miami FL USA.
Fredrik Jansson: Faculty of Civil Engineering and Geosciences, Department of Geoscience and Remote Sensing Delft University of Technology Delft Netherlands. ORCID
Todd R Jones: Department of Meteorology University of Reading Reading UK. ORCID
Marat Khairoutdinov: School of Marine and Atmospheric Sciences, and Institute for Advanced Computational Science, Stony Brook University State University of New York Stony Brook NY USA. ORCID
Daehyun Kim: Department of Atmospheric Sciences University of Washington Seattle WA USA. ORCID
Zane K Martin: Department of Applied Physics and Applied Mathematics Columbia University New York NY USA. ORCID
Shuhei Matsugishi: Atmosphere and Ocean Research Institute The University of Tokyo Kashiwa Japan.
Brian Medeiros: National Center for Atmospheric Research Boulder CO USA. ORCID
Hiroaki Miura: Department of Earth and Planetary Science, Graduate School of Science The University of Tokyo Tokyo Japan.
Yumin Moon: Department of Atmospheric Sciences University of Washington Seattle WA USA.
Sebastian K Müller: Max Planck Institute for Meteorology Hamburg Germany.
Tomoki Ohno: Japan Agency for Marine-Earth Science and Technology Yokohama Japan. ORCID
Max Popp: Laboratoire de Météorologie Dynamique (LMD)/IPSL/Sorbonne Université/CNRS/École Polytechnique/École Normale Supérieure Paris France. ORCID
Thara Prabhakaran: Indian Institute of Tropical Meteorology Pune India. ORCID
David Randall: Department of Atmospheric Science Colorado State University Fort Collins CO USA. ORCID
Rosimar Rios-Berrios: National Center for Atmospheric Research Boulder CO USA. ORCID
Nicolas Rochetin: Max Planck Institute for Meteorology Hamburg Germany. ORCID
Romain Roehrig: CNRM, Université de Toulouse, Météo-France, CNRS Toulouse France. ORCID
David M Romps: Department of Earth and Planetary Science University of California Berkeley CA USA.
James H Ruppert: Department of Meteorology and Atmospheric Science and Center for Advanced Data Assimilation and Predictability Techniques Pennsylvania State University University Park PA USA. ORCID
Masaki Satoh: Atmosphere and Ocean Research Institute The University of Tokyo Kashiwa Japan. ORCID
Levi G Silvers: School of Marine and Atmospheric Sciences Stony Brook University Stony Brook NY USA. ORCID
Martin S Singh: School of Earth, Atmosphere, and Environment Monash University Clayton Victoria Australia. ORCID
Bjorn Stevens: Max Planck Institute for Meteorology Hamburg Germany. ORCID
The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations.
