Constraints on Climate Sensitivity from Space-Based Measurements of Low-Cloud Reflection

被引:102
作者
Brient, Florent [1 ]
Schneider, Tapio [1 ,2 ]
机构
[1] Swiss Fed Inst Technol, Dept Earth Sci, Zurich, Switzerland
[2] CALTECH, 1200 E Calif Blvd, Pasadena, CA 91125 USA
基金
瑞士国家科学基金会;
关键词
FEEDBACK; SPREAD; TEMPERATURE; FUTURE; COVER;
D O I
10.1175/JCLI-D-15-0897.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Physical uncertainties in global-warming projections are dominated by uncertainties about how the fraction of incoming shortwave radiation that clouds reflect will change as greenhouse gas concentrations rise. Differences in the shortwave reflection by low clouds over tropical oceans alone account for more than half of the variance of the equilibrium climate sensitivity (ECS) among climate models, which ranges from 2.1 to 4.7 K. Space-based measurements now provide an opportunity to assess how well models reproduce temporal variations of this shortwave reflection on seasonal to interannual time scales. Here such space-based measurements are used to show that shortwave reflection by low clouds over tropical oceans decreases robustly when the underlying surface warms, for example, by -(0.96 +/- 0.22)% K-1 (90% confidence level) for de-seasonalized variations. Additionally, the temporal covariance of low-cloud reflection with temperature in historical simulations with current climate models correlates strongly (r = -0.67) with the models' ECS. Therefore, measurements of temporal low-cloud variations can be used to constrain ECS estimates based on climate models. An information-theoretic weighting of climate models by how well they reproduce the measured deseasonalized covariance of shortwave cloud reflection with temperature yields a most likely ECS estimate around 4.0 K; an ECS below 2.3K becomes very unlikely (90% confidence).
引用
收藏
页码:5821 / 5835
页数:15
相关论文
共 63 条
  • [1] The Dependence of Radiative Forcing and Feedback on Evolving Patterns of Surface Temperature Change in Climate Models
    Andrews, Timothy
    Gregory, Jonathan M.
    Webb, Mark J.
    [J]. JOURNAL OF CLIMATE, 2015, 28 (04) : 1630 - 1648
  • [2] Observational and Model Estimates of Cloud Amount Feedback over the Indian and Pacific Oceans
    Bellomo, Katinka
    Clement, Amy C.
    Norris, Joel R.
    Soden, Brian J.
    [J]. JOURNAL OF CLIMATE, 2014, 27 (02) : 925 - 940
  • [3] COSP Satellite simulation software for model assessment
    Bodas-Salcedo, A.
    Webb, M. J.
    Bony, S.
    Chepfer, H.
    Dufresne, J. -L.
    Klein, S. A.
    Zhang, Y.
    Marchand, R.
    Haynes, J. M.
    Pincus, R.
    John, V. O.
    [J]. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2011, 92 (08) : 1023 - 1043
  • [4] Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models
    Bony, S
    Dufresne, JL
    [J]. GEOPHYSICAL RESEARCH LETTERS, 2005, 32 (20) : 1 - 4
  • [5] Bowman A.W., 1997, Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-Plus Illustrations, V18
  • [6] Bretherton CS, 1997, J ATMOS SCI, V54, P148, DOI 10.1175/1520-0469(1997)054<0148:MTLTSA>2.0.CO
  • [7] 2
  • [8] Burnham KP., 2010, MODEL SELECTION MULT, DOI DOI 10.1007/B97636
  • [9] The GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP)
    Chepfer, H.
    Bony, S.
    Winker, D.
    Cesana, G.
    Dufresne, J. L.
    Minnis, P.
    Stubenrauch, C. J.
    Zeng, S.
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2010, 115
  • [10] Observational and Model Evidence for Positive Low-Level Cloud Feedback
    Clement, Amy C.
    Burgman, Robert
    Norris, Joel R.
    [J]. SCIENCE, 2009, 325 (5939) : 460 - 464