Cloud feedback in atmospheric general circulation models: An update

Cess, R. D.; Zhang, M. H.; Ingram, William; Potter, Gerald L.; Alekseev, V. N.; Barker, Howard; Cohen‐Solal, Emmanuelle; Colman, Robert; Dazlich, D. A.; Genio, Anthony D. Del; Dix, Martin; Dymnikov, V. P.; Esch, Monika; Fowler, Laura D.; Fraser, James Baillie; Galin, V. Ya.; Gates, W. Lawrence; Hack, James J.; Kiehl, J. T.; Treut, Hervé Le; Lo, K.; McAvaney, B. J.; Meleshko, V. P.; Morcrette, Jean‐Jacques; Randall, David A.; Roeckner, Erich; Royer, Jean‐François; Schlesinger, Michael E.; Sporyshev, P. V.; Timbal, Bertrand; Volodin, E. M.; Taylor, Karl E.; Wang, W.; Wetherald, R. T.

doi:10.1029/96jd00822

Cited by 277 publications

(169 citation statements)

References 8 publications

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“…The Mk2 model also took part in the FANGIO (Feedback Analysis for GCM Intercomparison and Observations) project, which was concerned with an evaluation of differences in cloud-radiation feedbacks between models (Cess et al 1996(Cess et al , 1997. There has been participation in similar investigations about the performance of the land surface schemes, for example Pitman et al (1993) and Chen et al (1997).…”

Section: International Intercomparisonsmentioning

confidence: 99%

Current and future latitudinal gradients in stream macroinvertebrate richness across North America

et al. 2014

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Section: International Intercomparisonsmentioning

confidence: 99%

Current and future latitudinal gradients in stream macroinvertebrate richness across North America

et al. 2014

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“…Their "climate sensitivities" (defined as the temperature increase for a doubling of GHG forcing) vary from as low as 1°C to as high as 5°C; the IPCC reports [1990, 1996a] gives a conventional range of 1.5°C to 4.5°C. An intercomparison of models has established that a major uncertainty relates to how clouds are treated [Cess et al, 1990[Cess et al, , 1996.Since they cannot be spatially resolved, they must be parameterized in some fashion. In many models, clouds add to the warming, but in others, clouds produce a cooling effect.…”

Section: Climate Modelsmentioning

confidence: 99%

Human contribution to climate change remains questionable

Singer

1999

EoS Transactions

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The principal focus of climate science is certainly atmospheric science and meteorology, but the subject involves many other areas of the Earth sciences as well as different disciplines, such as physics, chemistry and even biology. This complexity makes climate science both fascinating and controversial. It also undergoes rapid change as new facts and analyses emerge. Yet public interest in the possibility that human activities can change climate has become so intense that far‐reaching policies are instituted even before final judgments are possible.

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“…Marine boundary layer (MBL) cloud, as a strong modulator of the radiative energy 50 budget of the Earth-Atmosphere system, is a major source of uncertainty in future climate 51 change projections of the general circulation models (GCM) (Cess et al, 1996; Bony and 52 Dufresne, 2005). Improving MBL cloud simulations in the GCMs is one of the top priorities of 53 the climate modeling community.…”

mentioning

confidence: 99%

The Importance of Considering Sub-grid Cloud Variability When Using Satellite Observations to Evaluate the Cloud and Precipitation Simulations in Climate Models

Zhang¹,

Song²,

Ma³

et al. 2018

Preprint

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CloudSat to demonstrate the importance of considering the sub-grid variability of cloud and 34 precipitation when using the COSP to evaluate GCM simulations. We carry out two sensitivity 35 tests: SPCAM5 COSP and SPCAM5-Homogeneous COSP. In the SPCAM5 COSP run, the sub-36 grid cloud and precipitation properties from the embedded cloud resolving model (CRM) of 37 SPCAM5 are used to drive the COSP simulation, while in the SPCAM5-Homogeneous COSP 38 run only grid mean cloud and precipitation properties (i.e., no sub-grid variations) are given to 39 the COSP. We find that the warm rain signatures in the SPCAM5 COSP run agree with the 40 MODIS and CloudSat observations quite well. In contrast, the SPCAM5-Homogeneous COSP 41 run which ignores the sub-grid cloud variations, substantially overestimates the radar reflectivity 42 and probability of precipitation compared to the satellite observations, as well as the results from 43 the SPCAM5 COSP run. The significant differences between the two COSP runs demonstrate 44 that it is important to take into account the sub-grid variations of cloud and precipitation when 45 using COSP to evaluate the GCM to avoid confusing and misleading results. 46 47 48 Geosci. Model Dev. Discuss., https://doi

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Cloud feedback in atmospheric general circulation models: An update

Cited by 277 publications

References 8 publications

Current and future latitudinal gradients in stream macroinvertebrate richness across North America

Current and future latitudinal gradients in stream macroinvertebrate richness across North America

Human contribution to climate change remains questionable

The Importance of Considering Sub-grid Cloud Variability When Using Satellite Observations to Evaluate the Cloud and Precipitation Simulations in Climate Models

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