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Intercomparison and Interpretation of Climate Feedback Processes in 19 Atmospheric General Circulation Models

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Intercomparison and Interpretation of Climate Feedback Processes in 19 Atmospheric General Circulation Models JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 95, NO. D10, PAGES 16,601-16,615, SEPTEMBER 20, 1990 Intercomparison and Interpretation of Climate Feedback Processes in 19 Atmospheric General Circulation Models R. D. CESS,• G. L. POTTER,2 J.P. BLANCHET,3 G. J. BOER,3 A.D. DEL GENIO, 4 M. Dl•QUl•, 5 V. DYMNIKOV, 6 V. GALIN, 6 W. L. GATES,2 S. J. GHAN, 2 J. T. KIEHL, 7 A. A. LACiS, 4 H. LE TREUT, 8 Z.-X. LI, 8 X.-Z. LIANG, 9 B. J. MCAVANEY, lø V. P. MELESHKO,TM J. F. B. MITCHELL, 12J.-J. MORCRETTE,•3 D. A. RANDALL, TML. RIKUS, •ø E. ROECKNER,•5 J. F. ROYER, 5 U. SCHLESE,15 D. A. SHEININ, TMA. SLINGO,7 A. P. SOKOLOV,TM K. E. TAYLOR,2 W. M. WASHINGTON,7 R. T. WETHERALD, 16 I. YAGAI, 17AND M.-H. ZHANG 9 The need to understand differencesamong general circulation model projections of CO2-induced climatic change has motivated the present study, which provides an intercomparison and interpreta- tion of climate feedback processesin 19 atmosphericgeneral circulation models. This intercomparison uses sea surface temperature change as a surrogate for climate change. The interpretation of cloud-climate interactions is given special attention. A roughly threefold variation in one measure of global climate sensitivity is found among the 19 models. The important conclusion is that most of this variation is attributable to differences in the models' depiction of cloud feedback, a result that emphasizesthe need for improvements in the treatment of clouds in these models if they are ultimately to be used as reliable climate predictors. It is further emphasized that cloud feedback is the consequence of all interacting physical and dynamical processesin a general circulation model. The result of these processesis to produce changesin temperature, moisture distribution, and clouds which are integrated into the radiative responsetermed cloud feedback. 1. INTRODUCTION as predicted by five GCMs, might be partially attributable to Projected increases in the concentration of atmospheric the GCMs' differing control climates. Nevertheless, after carbon dioxide and other greenhouse gases are expected to accounting for this possibility, there still appear to be have an important impact on climate. The most comprehen- significantdifferences in the geographicaldistributions of the sive way to infer future climatic change associatedwith this simulated warmings. Furthermore, two recent investigations perturbation of atmospheric composition is by means of [Mitchell et al., 1989; J.P. Blanchet, private communica- three-dimensional general circulation models (GCMs). tion, 1989] suggest the importance of other factors with Schlesinger and Mitchell [1987] have, however, demon- regard to differences in global-mean warming. strated that several existing GCMs simulate climate re- An understanding of the reasons for these differences sponsesto increasingCO2 that differ considerably.Cess and requires a systematic examination and intercomparison of Potter [1988], following a suggestionby Speltnan and Man- the parameterizationsand processesin different models. If a abe [1984], indicate that differences in global-mean warming, broad spectrum of modeling groups are to participate in such a GCM intercomparison, simplicity is a necessary condition. 1StateUniversity of New York, StonyBrook. With this in mind, Cess and Potter [1988] proposed a 2LawrenceLivermore National Laboratory, Livermore, Califor- nia. procedure in which perturbations in sea surface temperature 3CanadianClimate Centre, Downsview, Ontario, Canada. serve as a surrogate climate change for the purpose of both 4NASAGoddard Institute for SpaceStudies, New York. intercomparing and understanding climate feedback pro- 5Directionde la M6t6orologieNationale, Toulouse, France. cesses in atmospheric GCMs. They further illustrated that 6USSRAcademy of Sciences,Moscow. 7NationalCenter for AtmosphericResearch, Boulder, Colorado. cloud feedback could readily be inferred by separately 8Laboratoirede M6t6orologieDynamique, Paris, France. treating clear and overcast regions within a model. 9Instituteof AtmosphericPhysics, Beijing, China. The purpose of the present study is to use this approach to løBureauof MeteorologyResearch Centre, Melbourne, Australia. liMain GeophysicalObservatory, Leningrad, USSR. interpret and intercompare atmospheric climate feedback 12UnitedKingdom Meteorological Office, Bracknell, Berkshire, processesin 19 different GCMs, with particular emphasis on England. understandingthe role of clouds. As emphasized by Cess et 13EuropeanCentre for Medium-RangeWeather Forecasts, Read- al. [1989], in an early summary of this intercomparison, ing, Berkshire, England. 14ColoradoState University, Fort Collins. cloud feedback is the cause of much of the intermodel 15Universityof Hamburg,Hamburg, Germany. differencesin climate sensitivity. The important point here is 16NationalOceanic and Atmospheric Administration, Geophysi- not simply to illustrate differences among models but to cal Fluid Dynamics Laboratory, Princeton, New Jersey. understand why these differences occur. As will become 17MeteorologicalResearch Institute, Tsukuba, Japan. evident, it is especially important to understand that some Copyright 1990 by the American Geophysical Union. models produce similar climate sensitivities as a conse- Paper number 90JD01219. quence of very different cloud feedback components that 0148-0227/90/90JD-01219505.00 compensate to produce similar net feedbacks. 16,601 16,602 CESS ET AL.' CLIMATE FEEDBACK IN 19 GENERAL CIRCULATION MODELS 2. INTERCOMPARISON AND INTERPRETATION system, which is constant in this case. It then follows that METHODOLOGY AF/AT•= 4F/T• = 3.3W m-2 K -• for conditionstypical of Earth(F = 240W m-2 and T• = 288K), so that in the Many facets of the climate system are not well under- absence of interactive feedback mechanisms stood, and thus the uncertainties in modeling atmospheric, • . cryospheric, and oceamc interactions are large. In evaluat- 0.3 K m2 W- 1 (4) ing the differences among models, attention has been fo- cused here on atmospheric processes,because these uncer- A well-known positive feedback mechanism is water va- tainties must be understood before others can be addressed. por feedback [Manabe and Wetherald, 1967], in which a For simplicity, emphasisis placed solely on global-average warmer atmospherecontains more water vapor, which as a quantities, and the conventionalinterpretation is adoptedof greenhousegas amplifiesthe initial warming. Climate models climate change as a two-stage process:forcing and response that containthis positivefeedback typically give AF/ATs •- [Cess and Potter, 1988]. This concept of global-average 2.2 W m-2 K -•. In addition,the increasedwater vapor forcing and responsehas proven useful in earlier interpreta- increasesthe atmospheric absorption of solar radiation, and tions of cloud feedback. For example, by performing two for a typical model this positive feedbackyields AQ/ATs •-- 6CM simulationsfor a doublingof atmosphericCO2 con- 0.2 W m-2 K -• . Thuswith the inclusionof watervapor centration, one with computed clouds and the other with feedback the sensitivity parameter is increased from that clouds that were invariant to the change in climate, Wether- given in (4) to ald and Manabe [1988] have suggestedthat cloud feedback amplifies global warming by the factor 1.3. A somewhat 0.5 K m2 W -1 (5) larger amplification (1.8) is found from the study by Hansen et al. [1984], who used a one-dimensional climate model to Whereas water vapor feedback is straightforward to un- evaluate climate feedback mechanisms within a different derstand, cloud feedback is a far more complex phenome- 6CM. A further discussionof these resultswill be presented non. There are several ways that clouds can produce feed- in section 6. back mechanisms. For example, if global cloud amount The global-meandirect radiative forcing G of the surface- decreasesbecause of climate warming, as occurred in sim- atmosphere system is evaluated by holding all other climate ulations with the 19 GCMs we employed, then this decrease parameters fixed. It is this quantity that induces the ensuing reduces the infrared greenhouseeffect due to clouds. Thus climate change, and physically, it representsa changein the as the Earth warms, it is able to emit infrared radiation more net (solar plus infrared) radiative flux at the top of the efficiently, moderating the global warming and so acting as a atmosphere(TOA). For an increasein the CO2 concentra- negative climate feedback mechanism. But there is a related tion of the atmosphere, to cite one example, G is the positive feedback; the solar radiation absorbed by the sur- reduction in the emitted TOA infrared flux resulting solely face-atmosphere system increases because the diminished from the CO2 increase,and this reductionresults in a heating cloud amount causes a reduction of reflected solar radiation of the surface-atmospheresystem. The responseprocess is by the atmosphere. The situation is further complicated by the change in climate that is then necessary to restore the climate-inducedchanges in both cloud vertical structure and TOA radiation balance, such that cloud optical properties, which result in additional infrared and solar feedbacks [Cess and Potter, 1988]. G = AF- AQ (1) In this intercomparison, cloud effects were isolated by separately averaging a model's clear-sky TOA fluxes [Char- where F and Q respectively denote the global-meanemitted infrared and net downward solar fluxes at the TOA. Thus AF lock and Ramanathan, 1985; Ramanathan, 1987; Cess and
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