scholarly journals Seasonal Variations of Climate Feedbacks in the NCAR CCSM3

2011 ◽  
Vol 24 (13) ◽  
pp. 3433-3444 ◽  
Author(s):  
Patrick C. Taylor ◽  
Robert G. Ellingson ◽  
Ming Cai

Abstract This study investigates the annual cycle of radiative contributions to global climate feedbacks. A partial radiative perturbation (PRP) technique is used to diagnose monthly radiative perturbations at the top of atmosphere (TOA) due to CO2 forcing; surface temperature response; and water vapor, cloud, lapse rate, and surface albedo feedbacks using NCAR Community Climate System Model, version 3 (CCSM3) output from a Special Report on Emissions Scenarios (SRES) A1B emissions-scenario-forced climate simulation. The seasonal global mean longwave TOA radiative feedback was found to be minimal. However, the global mean shortwave (SW) TOA cloud and surface albedo radiative perturbations exhibit large seasonality. The largest contributions to the negative SW cloud feedback occur during summer in each hemisphere, marking the largest differences with previous results. Results suggest that intermodel spread in climate sensitivity may occur, partially from cloud and surface albedo feedback seasonality differences. Further, links between the climate feedback and surface temperature response seasonality are investigated, showing a strong relationship between the seasonal climate feedback distribution and the seasonal surface temperature response.

2013 ◽  
Vol 26 (13) ◽  
pp. 4518-4534 ◽  
Author(s):  
Kyle C. Armour ◽  
Cecilia M. Bitz ◽  
Gerard H. Roe

Abstract The sensitivity of global climate with respect to forcing is generally described in terms of the global climate feedback—the global radiative response per degree of global annual mean surface temperature change. While the global climate feedback is often assumed to be constant, its value—diagnosed from global climate models—shows substantial time variation under transient warming. Here a reformulation of the global climate feedback in terms of its contributions from regional climate feedbacks is proposed, providing a clear physical insight into this behavior. Using (i) a state-of-the-art global climate model and (ii) a low-order energy balance model, it is shown that the global climate feedback is fundamentally linked to the geographic pattern of regional climate feedbacks and the geographic pattern of surface warming at any given time. Time variation of the global climate feedback arises naturally when the pattern of surface warming evolves, actuating feedbacks of different strengths in different regions. This result has substantial implications for the ability to constrain future climate changes from observations of past and present climate states. The regional climate feedbacks formulation also reveals fundamental biases in a widely used method for diagnosing climate sensitivity, feedbacks, and radiative forcing—the regression of the global top-of-atmosphere radiation flux on global surface temperature. Further, it suggests a clear mechanism for the “efficacies” of both ocean heat uptake and radiative forcing.


2013 ◽  
Vol 26 (18) ◽  
pp. 7023-7043 ◽  
Author(s):  
Patrick C. Taylor ◽  
Ming Cai ◽  
Aixue Hu ◽  
Jerry Meehl ◽  
Warren Washington ◽  
...  

Abstract Polar surface temperatures are expected to warm 2–3 times faster than the global-mean surface temperature: a phenomenon referred to as polar warming amplification. Therefore, understanding the individual process contributions to the polar warming is critical to understanding global climate sensitivity. The Coupled Feedback Response Analysis Method (CFRAM) is applied to decompose the annual- and zonal-mean vertical temperature response within a transient 1% yr−1 CO2 increase simulation of the NCAR Community Climate System Model, version 4 (CCSM4), into individual radiative and nonradiative climate feedback process contributions. The total transient annual-mean polar warming amplification (amplification factor) at the time of CO2 doubling is +2.12 (2.3) and +0.94 K (1.6) in the Northern and Southern Hemisphere, respectively. Surface albedo feedback is the largest contributor to the annual-mean polar warming amplification accounting for +1.82 and +1.04 K in the Northern and Southern Hemisphere, respectively. Net cloud feedback is found to be the second largest contributor to polar warming amplification (about +0.38 K in both hemispheres) and is driven by the enhanced downward longwave radiation to the surface resulting from increases in low polar water cloud. The external forcing and atmospheric dynamic transport also contribute positively to polar warming amplification: +0.29 and +0.32 K, respectively. Water vapor feedback contributes negatively to polar warming amplification because its induced surface warming is stronger in low latitudes. Ocean heat transport storage and surface turbulent flux feedbacks also contribute negatively to polar warming amplification. Ocean heat transport and storage terms play an important role in reducing the warming over the Southern Ocean and Northern Atlantic Ocean.


2017 ◽  
Vol 114 (50) ◽  
pp. 13126-13131 ◽  
Author(s):  
Paulo Ceppi ◽  
Jonathan M. Gregory

Climate feedbacks generally become smaller in magnitude over time under CO2 forcing in coupled climate models, leading to an increase in the effective climate sensitivity, the estimated global-mean surface warming in steady state for doubled CO2. Here, we show that the evolution of climate feedbacks in models is consistent with the effect of a change in tropospheric stability, as has recently been hypothesized, and the latter is itself driven by the evolution of the pattern of sea-surface temperature response. The change in climate feedback is mainly associated with a decrease in marine tropical low cloud (a more positive shortwave cloud feedback) and with a less negative lapse-rate feedback, as expected from a decrease in stability. Smaller changes in surface albedo and humidity feedbacks also contribute to the overall change in feedback, but are unexplained by stability. The spatial pattern of feedback changes closely matches the pattern of stability changes, with the largest increase in feedback occurring in the tropical East Pacific. Relationships qualitatively similar to those in the models among sea-surface temperature pattern, stability, and radiative budget are also found in observations on interannual time scales. Our results suggest that constraining the future evolution of sea-surface temperature patterns and tropospheric stability will be necessary for constraining climate sensitivity.


2011 ◽  
Vol 24 (11) ◽  
pp. 2737-2753 ◽  
Author(s):  
Patrick C. Taylor ◽  
Robert G. Ellingson ◽  
Ming Cai

Abstract This study performs offline, partial radiative perturbation calculations to determine the geographical distributions of climate feedbacks contributing to the top-of-atmosphere (TOA) radiative energy budget. These radiative perturbations are diagnosed using monthly mean model output from the NCAR Community Climate System Model version 3 (CCSM3.0) forced with the Special Report Emissions Scenario (SRES) A1B emission scenario. The Monte Carlo Independent Column Approximation (MCICA) technique with a maximum–random overlap rule is used to sample monthly mean cloud frequency profiles to perform the radiative transfer calculations. It is shown that the MCICA technique provides a good estimate of all feedback sensitivity parameters. The radiative perturbation results are used to investigate the spatial variability of model feedbacks showing that the shortwave cloud and lapse rate feedbacks exhibit the most and second most spatial variability, respectively. It has been shown that the model surface temperature response is highly correlated with the change in the TOA net flux, and that the latter is largely determined by the total feedback spatial pattern rather than the external forcing. It is shown by representing the change in the TOA net flux as a linear combination of individual feedback radiative perturbations that the lapse rate explains the most spatial variance of the surface temperature response. Feedback spatial patterns are correlated with the model response and other feedback spatial patterns to investigate these relationships. The results indicate that the model convective response is strongly correlated with cloud and water vapor feedbacks, but the lapse rate feedback geographic distribution is strongly correlated with the climatological distribution of convection. The implication for the water vapor–lapse rate anticorrelation is discussed.


2015 ◽  
Vol 28 (4) ◽  
pp. 1630-1648 ◽  
Author(s):  
Timothy Andrews ◽  
Jonathan M. Gregory ◽  
Mark J. Webb

Abstract Experiments with CO2 instantaneously quadrupled and then held constant are used to show that the relationship between the global-mean net heat input to the climate system and the global-mean surface air temperature change is nonlinear in phase 5 of the Coupled Model Intercomparison Project (CMIP5) atmosphere–ocean general circulation models (AOGCMs). The nonlinearity is shown to arise from a change in strength of climate feedbacks driven by an evolving pattern of surface warming. In 23 out of the 27 AOGCMs examined, the climate feedback parameter becomes significantly (95% confidence) less negative (i.e., the effective climate sensitivity increases) as time passes. Cloud feedback parameters show the largest changes. In the AOGCM mean, approximately 60% of the change in feedback parameter comes from the tropics (30°N–30°S). An important region involved is the tropical Pacific, where the surface warming intensifies in the east after a few decades. The dependence of climate feedbacks on an evolving pattern of surface warming is confirmed using the HadGEM2 and HadCM3 atmosphere GCMs (AGCMs). With monthly evolving sea surface temperatures and sea ice prescribed from its AOGCM counterpart, each AGCM reproduces the time-varying feedbacks, but when a fixed pattern of warming is prescribed the radiative response is linear with global temperature change or nearly so. It is also demonstrated that the regression and fixed-SST methods for evaluating effective radiative forcing are in principle different, because rapid SST adjustment when CO2 is changed can produce a pattern of surface temperature change with zero global mean but nonzero change in net radiation at the top of the atmosphere (~−0.5 W m−2 in HadCM3).


2014 ◽  
Vol 27 (8) ◽  
pp. 2912-2930 ◽  
Author(s):  
Xiaoliang Song ◽  
Guang J. Zhang ◽  
Ming Cai

Abstract The climate feedback–response analysis method (CFRAM) was applied to 10-yr hourly output of the NCAR Community Climate System Model, version 3, using the slab ocean model (CCSM3-SOM), to analyze the strength and spatial distribution of climate feedbacks and to characterize their contributions to the global and regional surface temperature Ts changes in response to a doubling of CO2. The global mean bias in the sum of partial Ts changes associated with the CO2 forcing, and each feedback derived with the CFRAM analysis is about 2% of Ts change obtained directly from the CCSM3-SOM simulations. The pattern correlation between the two is 0.94, indicating that the CFRAM analysis using hourly model output is accurate and thus is appropriate for quantifying the contributions of climate feedback to the formation of global and regional warming patterns. For global mean Ts, the largest contributor to the warming is water vapor feedback, followed by the direct CO2 forcing and albedo feedback. The albedo feedback exhibits the largest spatial variation, followed by shortwave cloud feedback. In terms of pattern correlation and RMS difference with the modeled global surface warming, longwave cloud feedback contributes the most. On zonal average, albedo feedback is the largest contributor to the stronger warming in high latitudes than in the tropics. The longwave cloud feedback further amplifies the latitudinal warming contrast. Both the land–ocean warming difference and contributions of climate feedbacks to it vary with latitude. Equatorward of 50°, shortwave cloud feedback and dynamical advection are the two largest contributors. The land–ocean warming difference on the hemispheric scale is mainly attributable to longwave cloud feedback and convection.


2014 ◽  
Vol 27 (12) ◽  
pp. 4433-4450 ◽  
Author(s):  
Rune G. Graversen ◽  
Peter L. Langen ◽  
Thorsten Mauritsen

Abstract A vertically nonuniform warming of the troposphere yields a lapse rate feedback by altering the infrared irradiance to space relative to that of a vertically uniform tropospheric warming. The lapse rate feedback is negative at low latitudes, as a result of moist convective processes, and positive at high latitudes, due to stable stratification conditions that effectively trap warming near the surface. It is shown that this feedback pattern leads to polar amplification of the temperature response induced by a radiative forcing. The results are obtained by suppressing the lapse rate feedback in the Community Climate System Model, version 4 (CCSM4). The lapse rate feedback accounts for 15% of the Arctic amplification and 20% of the amplification in the Antarctic region. The fraction of the amplification that can be attributed to the surface albedo feedback, associated with melting of snow and ice, is 40% in the Arctic and 65% in Antarctica. It is further found that the surface albedo and lapse rate feedbacks interact considerably at high latitudes to the extent that they cannot be considered independent feedback mechanisms at the global scale.


2006 ◽  
Vol 19 (2) ◽  
pp. 193-209 ◽  
Author(s):  
Markus Stowasser ◽  
Kevin Hamilton ◽  
George J. Boer

Abstract The climatic response to a 5% increase in solar constant is analyzed in three coupled global ocean–atmosphere general circulation models, the NCAR Climate System Model version 1 (CSM1), the Community Climate System Model version 2 (CCSM2), and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled General Circulation Model version 3 (CGCM3). For this simple perturbation the quantitative values of the radiative climate forcing at the top of the atmosphere can be determined very accurately simply from a knowledge of the shortwave fluxes in the control run. The climate sensitivity and the geographical pattern of climate feedbacks, and of the shortwave, longwave, clear-sky, and cloud components in each model, are diagnosed as the climate evolves. After a period of adjustment of a few years, both the magnitude and pattern of the feedbacks become reasonably stable with time, implying that they may be accurately determined from relatively short integrations. The global-mean forcing at the top of the atmosphere due to the solar constant change is almost identical in the three models. The exact value of the forcing in each case is compared with that inferred by regressing annual-mean top-of-the-atmosphere radiative imbalance against mean surface temperature change. This regression approach yields a value close to the directly diagnosed forcing for the CCCma model, but a value only within about 25% of the directly diagnosed forcing for the two NCAR models. These results indicate that this regression approach may have some practical limitation in its application, at least for some models. The global climate sensitivities differ among the models by almost a factor of 2, and, despite an overall apparent similarity, the spatial patterns of the climate feedbacks are only modestly correlated among the three models. An exception is the clear-sky shortwave feedback, which agrees well in both magnitude and spatial pattern among the models. The biggest discrepancies are in the shortwave cloud feedback, particularly in the tropical and subtropical regions where it is strongly negative in the NCAR models but weakly positive in the CCCma model. Almost all of the difference in the global-mean total feedback (and climate sensitivity) among the models is attributable to the shortwave cloud feedback component. All three models exhibit a region of positive feedback in the equatorial Pacific, which is surrounded by broad areas of negative feedback. These positive feedback regions appear to be associated with a local maximum of the surface warming. However, the models differ in the zonal structure of this surface warming, which ranges from a mean El Niño–like warming in the eastern Pacific in the CCCma model to a far-western Pacific maximum of warming in the NCAR CCSM2 model. A separate simulation with the CCSM2 model, in which these tropical Pacific zonal gradients of surface warming are artificially suppressed, shows no region of positive radiative feedback in the tropical Pacific. However, the global-mean feedback is only modestly changed in this constrained run, suggesting that the processes that produce the positive feedback in the tropical Pacific region may not contribute importantly to global-mean feedback and climate sensitivity.


2016 ◽  
Vol 9 (7) ◽  
pp. 2459-2470 ◽  
Author(s):  
Ryan Reynolds Neely III ◽  
Andrew J. Conley ◽  
Francis Vitt ◽  
Jean-François Lamarque

Abstract. Here we describe an updated parameterization for prescribing stratospheric aerosol in the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM1). The need for a new parameterization is motivated by the poor response of the CESM1 (formerly referred to as the Community Climate System Model, version 4, CCSM4) simulations contributed to the Coupled Model Intercomparison Project 5 (CMIP5) to colossal volcanic perturbations to the stratospheric aerosol layer (such as the 1991 Pinatubo eruption or the 1883 Krakatau eruption) in comparison to observations. In particular, the scheme used in the CMIP5 simulations by CESM1 simulated a global mean surface temperature decrease that was inconsistent with the GISS Surface Temperature Analysis (GISTEMP), NOAA's National Climatic Data Center, and the Hadley Centre of the UK Met Office (HADCRUT4). The new parameterization takes advantage of recent improvements in historical stratospheric aerosol databases to allow for variations in both the mass loading and size of the prescribed aerosol. An ensemble of simulations utilizing the old and new schemes shows CESM1's improved response to the 1991 Pinatubo eruption. Most significantly, the new scheme more accurately simulates the temperature response of the stratosphere due to local aerosol heating. Results also indicate that the new scheme decreases the global mean temperature response to the 1991 Pinatubo eruption by half of the observed temperature change, and modelled climate variability precludes statements as to the significance of this change.


2021 ◽  
Vol 34 (2) ◽  
pp. 755-772
Author(s):  
Patrik L. Pfister ◽  
Thomas F. Stocker

AbstractThe global-mean climate feedback quantifies how much the climate system will warm in response to a forcing such as increased CO2 concentration. Under a constant forcing, this feedback becomes less negative (increasing) over time in comprehensive climate models, which has been attributed to increases in cloud and lapse-rate feedbacks. However, out of eight Earth system models of intermediate complexity (EMICs) not featuring interactive clouds, two also simulate such a feedback increase: Bern3D-LPX and LOVECLIM. Using these two models, we investigate the causes of the global-mean feedback increase in the absence of cloud feedbacks. In both models, the increase is predominantly driven by processes in the Southern Ocean region. In LOVECLIM, the global-mean increase is mainly due to a local longwave feedback increase in that region, which can be attributed to lapse-rate changes. It is enhanced by the slow atmospheric warming above the Southern Ocean, which is delayed due to regional ocean heat uptake. In Bern3D-LPX, this delayed regional warming is the main driver of the global-mean feedback increase. It acts on a near-constant local feedback pattern mainly determined by the sea ice–albedo feedback. The global-mean feedback increase is limited by the availability of sea ice: faster Southern Ocean sea ice melting due to either stronger forcing or higher equilibrium climate sensitivity (ECS) reduces the increase of the global mean feedback in Bern3D-LPX. In the highest-ECS simulation with 4 × CO2 forcing, the feedback even becomes more negative (decreasing) over time. This reduced ice–albedo feedback due to sea ice depletion is a plausible mechanism for a decreasing feedback also in high-forcing simulations of other models.


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