Clouds and Convective Self-Aggregation in a Multimodel Ensemble of Radiative-Convective Equilibrium Simulations

被引:108
|
作者
Wing, Allison A. [1 ]
Stauffer, Catherine L. [1 ]
Becker, Tobias [2 ]
Reed, Kevin A. [3 ]
Ahn, Min-Seop [4 ]
Arnold, Nathan P. [5 ]
Bony, Sandrine [6 ]
Branson, Mark [7 ]
Bryan, George H. [8 ]
Chaboureau, Jean-Pierre [9 ]
De Roode, Stephan R. [10 ]
Gayatri, Kulkarni [11 ]
Hohenegger, Cathy [2 ]
Hu, I-Kuan [12 ]
Jansson, Fredrik [10 ,13 ]
Jones, Todd R. [14 ]
Khairoutdinov, Marat [3 ,15 ]
Kim, Daehyun [4 ]
Martin, Zane K. [16 ]
Matsugishi, Shuhei [17 ]
Medeiros, Brian [8 ]
Miura, Hiroaki [18 ]
Moon, Yumin [4 ]
Mueller, Sebastian K. [2 ]
Ohno, Tomoki [19 ]
Popp, Max [20 ]
Prabhakaran, Thara [11 ]
Randall, David [7 ]
Rios-Berrios, Rosimar [8 ]
Rochetin, Nicolas [2 ,20 ]
Roehrig, Romain [21 ]
Romps, David M. [22 ,23 ]
Ruppert, James H., Jr. [24 ,25 ]
Satoh, Masaki [17 ]
Silvers, Levi G. [3 ]
Singh, Martin S. [26 ]
Stevens, Bjorn [2 ]
Tomassini, Lorenzo [27 ]
van Heerwaarden, Chiel C. [28 ]
Wang, Shuguang [16 ]
Zhao, Ming [29 ]
机构
[1] Florida State Univ, Dept Earth Ocean & Atmospher Sci, Tallahassee, FL 32306 USA
[2] Max Planck Inst Meteorol, Hamburg, Germany
[3] SUNY Stony Brook, Sch Marine & Atmospher Sci, Stony Brook, NY 11794 USA
[4] Univ Washington, Dept Atmospher Sci, Seattle, WA 98195 USA
[5] NASA, Global Modeling & Assimilat Off, Goddard Space Flight Ctr, Greenbelt, MD USA
[6] Sorbonne Univ, IPSL, Lab Meteorol Dynam LMD, CNRS, Paris, France
[7] Colorado State Univ, Dept Atmospher Sci, Ft Collins, CO 80523 USA
[8] Natl Ctr Atmospher Res, POB 3000, Boulder, CO 80307 USA
[9] Univ Toulouse, Lab Aerol, UPS, CNRS, Toulouse, France
[10] Delft Univ Technol, Fac Civil Engn & Geosci, Dept Geosci & Remote Sensing, Delft, Netherlands
[11] Indian Inst Trop Meteorol, Pune, Maharashtra, India
[12] Univ Miami, Rosenstiel Sch Marine & Atmospher Sci, 4600 Rickenbacker Causeway, Miami, FL 33149 USA
[13] Ctr Wiskunde & Informat, Amsterdam, Netherlands
[14] Univ Reading, Dept Meteorol, Reading, Berks, England
[15] SUNY Stony Brook, Inst Adv Computat Sci, Stony Brook, NY 11794 USA
[16] Columbia Univ, Dept Appl Phys & Appl Math, New York, NY USA
[17] Univ Tokyo, Atmosphere & Ocean Res Inst, Kashiwa, Chiba, Japan
[18] Univ Tokyo, Grad Sch Sci, Dept Earth & Planetary Sci, Tokyo, Japan
[19] Japan Agcy Marine Earth Sci & Technol, Yokohama, Kanagawa, Japan
[20] Sorbonne Univ, Ecole Normale Super, IPSL, Lab Meteorol Dynam LMD,CNRS,Ecole Polytech, Paris, France
[21] Univ Toulouse, CNRS, Meteo France, CNRM, Toulouse, France
[22] Univ Calif Berkeley, Dept Earth & Planetary Sci, Berkeley, CA 94720 USA
[23] Lawrence Berkeley Natl Lab, Climate & Ecosyst Sci Div, Berkeley, CA USA
[24] Penn State Univ, Dept Meteorol & Atmospher Sci, University Pk, PA 16802 USA
[25] Penn State Univ, Ctr Adv Data Assimilat & Predictabil Tech, University Pk, PA 16802 USA
[26] Monash Univ, Sch Earth Atmosphere & Environm, Clayton, Vic, Australia
[27] Met Off, Exeter, Devon, England
[28] Wageningen Univ, Meteorol & Air Qual Grp, Wageningen, Netherlands
[29] NOAA, Geophys Fluid Dynam Lab, Princeton, NJ USA
基金
荷兰研究理事会; 澳大利亚研究理事会; 美国国家科学基金会; 欧盟地平线“2020”; 英国自然环境研究理事会;
关键词
convection; clouds; climate sensitivity; self-aggregation; radiative-convective equilibrium; cloud feedbacks; LARGE-SCALE ORGANIZATION; SEA-SURFACE TEMPERATURE; TROPICAL CONVECTION; CLIMATE SENSITIVITY; PHYSICAL-MECHANISMS; DIABATIC PROCESSES; ANVIL CLOUDS; MODEL; EXPLICIT; PROJECT;
D O I
10.1029/2020MS002138
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
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.
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页数:38
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