scholarly journals Climate Sensitivity of the Community Climate System Model, Version 4

2012 ◽  
Vol 25 (9) ◽  
pp. 3053-3070 ◽  
Author(s):  
C. M. Bitz ◽  
K. M. Shell ◽  
P. R. Gent ◽  
D. A. Bailey ◽  
G. Danabasoglu ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Sensitivity ◽  
Ocean Model ◽  
System Model ◽  
Climate Response ◽  
Climate System Model ◽  
Equilibrium Climate Sensitivity ◽  
Model Version ◽  
Slab Ocean ◽  
Global Mean

Equilibrium climate sensitivity of the Community Climate System Model, version 4 (CCSM4) is 3.20°C for 1° horizontal resolution in each component. This is about a half degree Celsius higher than in the previous version (CCSM3). The transient climate sensitivity of CCSM4 at 1° resolution is 1.72°C, which is about 0.2°C higher than in CCSM3. These higher climate sensitivities in CCSM4 cannot be explained by the change to a preindustrial baseline climate. This study uses the radiative kernel technique to show that, from CCSM3 to CCSM4, the global mean lapse-rate feedback declines in magnitude and the shortwave cloud feedback increases. These two warming effects are partially canceled by cooling because of slight decreases in the global mean water vapor feedback and longwave cloud feedback from CCSM3 to CCSM4. A new formulation of the mixed layer, slab-ocean model in CCSM4 attempts to reproduce the SST and sea ice climatology from an integration with a full-depth ocean, and it is integrated with a dynamic sea ice model. These new features allow an isolation of the influence of ocean dynamical changes on the climate response when comparing integrations with the slab ocean and full-depth ocean. The transient climate response of the full-depth ocean version is 0.54 of the equilibrium climate sensitivity when estimated with the new slab-ocean model version for both CCSM3 and CCSM4. The authors argue the ratio is the same in both versions because they have about the same zonal mean pattern of change in ocean surface heat flux, which broadly resembles the zonal mean pattern of net feedback strength.

scholarly journals Equilibrium Climate Sensitivity: Is It Accurate to Use a Slab Ocean Model?

2009 ◽  
Vol 22 (9) ◽  
pp. 2494-2499 ◽  
Author(s):  
Gokhan Danabasoglu ◽  
Peter R. Gent
Keyword(s):  
Carbon Dioxide ◽  
Climate Sensitivity ◽  
Climate Model ◽  
Temperature Response ◽  
Accurate Estimate ◽  
Ocean Model ◽  
Climate System Model ◽  
Equilibrium Climate Sensitivity ◽  
Model Version ◽  
Slab Ocean

Abstract The equilibrium climate sensitivity of a climate model is usually defined as the globally averaged equilibrium surface temperature response to a doubling of carbon dioxide. This is virtually always estimated in a version with a slab model for the upper ocean. The question is whether this estimate is accurate for the full climate model version, which includes a full-depth ocean component. This question has been answered for the low-resolution version of the Community Climate System Model, version 3 (CCSM3). The answer is that the equilibrium climate sensitivity using the full-depth ocean model is 0.14°C higher than that using the slab ocean model, which is a small increase. In addition, these sensitivity estimates have a standard deviation of nearly 0.1°C because of interannual variability. These results indicate that the standard practice of using a slab ocean model does give a good estimate of the equilibrium climate sensitivity of the full CCSM3. Another question addressed is whether the effective climate sensitivity is an accurate estimate of the equilibrium climate sensitivity. Again the answer is yes, provided that at least 150 yr of data from the doubled carbon dioxide run are used.

Mechanisms affecting equilibrium climate sensitivity in the PlaSim Earth System Model with different ocean model configurations

2020 ◽  
Author(s):  
Michela Angeloni ◽  
Elisa Palazzi ◽  
Jost von Hardenberg
Keyword(s):  
Sea Ice ◽  
Mixed Layer ◽  
Climate Sensitivity ◽  
Ocean Model ◽  
Earth System Model ◽  
System Model ◽  
Cmip5 Models ◽  
Earth System ◽  
Feedback Parameter ◽  
Equilibrium Climate Sensitivity

<p>The equilibrium climate sensitivity (ECS) of a state-of-the-art Earth System Model of intermediate complexity, the Planet Simulator (PlaSim), is determined under three tuned configurations, in which the model is coupled with a simple Mixed Layer (ML) or with the full 3D Large Scale Geostrophic (LSG) ocean model, at two horizontal resolutions, T21 (600 km) and T42 (300 km). Sensitivity experiments with doubled and quadrupled CO<sub>2</sub> were run, using either dynamic or prescribed sea ice. The resulting ECS using dynamic sea ice is 6.3 K for PlaSim-ML T21, 5.4 K for PlaSim-ML T42 and a much smaller 4.2 K for PlaSim-LSG T21. A systematic comparison between simulations with dynamic and prescribed sea ice helps to identify a strong contribution of sea ice to the value of the feedback parameter and of the climate sensitivity. Additionally, Antarctic sea ice is underestimated in PlaSim-LSG leading to a further reduction of ECS when the LSG ocean is used. The ECS of ML experiments is generally large compared with current estimates of equilibrium climate sensitivity in CMIP5 models and other EMICs: a relevant observation is that the choice of the ML horizontal diffusion coefficient, and therefore of the parameterized meridional heat transport and in turn the resulting equator-poles temperature gradient, plays an important role in controlling the ECS of the PlaSim-ML configurations. This observation should be possibly taken into account when evaluating ECS estimates in models with a mixed layer ocean. The configuration of PlaSim with the LSG ocean shows very different AMOC regimes, including 250-year oscillations and a complete shutdown of meridional transport, which depend on the ocean vertical diffusion profile and the CO<sub>2</sub> forcing conditions. These features can be explored in the framework of tipping points: the simplified and parameterized form of the climate system components included in PlaSim makes this model a suitable tool to study the transitions occurring in the Earth system in presence of critical points.</p>

scholarly journals The Climate Sensitivity of the Community Climate System Model Version 3 (CCSM3)

2006 ◽  
Vol 19 (11) ◽  
pp. 2584-2596 ◽  
Author(s):  
Jeffrey T. Kiehl ◽  
Christine A. Shields ◽  
James J. Hack ◽  
William D. Collins
Keyword(s):  
Carbon Dioxide ◽  
High Resolution ◽  
Surface Temperature ◽  
Climate Sensitivity ◽  
Horizontal Resolution ◽  
System Model ◽  
Climate Response ◽  
Community Climate System Model ◽  
Transient Climate Response ◽  
Climate System Model

Abstract The climate sensitivity of the Community Climate System Model (CCSM) is described in terms of the equilibrium change in surface temperature due to a doubling of carbon dioxide in a slab ocean version of the Community Atmosphere Model (CAM) and the transient climate response, which is the surface temperature change at the point of doubling of carbon dioxide in a 1% yr−1 CO2 simulation with the fully coupled CCSM. For a fixed atmospheric horizontal resolution across model versions, we show that the equilibrium sensitivity has monotonically increased across CSM1.4, CCSM2, to CCSM3 from 2.01° to 2.27° to 2.47°C, respectively. The transient climate response for these versions is 1.44° to 1.09° to 1.48°C, respectively. Using climate feedback analysis, it is shown that both clear-sky and cloudy-sky processes have contributed to the changes in transient climate response. The dependence of these sensitivities on horizontal resolution is also explored. The equilibrium sensitivity of the high-resolution (T85) version of CCSM3 is 2.71°C, while the equilibrium response for the low-resolution model (T31) is 2.32°C. It is shown that the shortwave cloud response of the high-resolution version of the CCSM3 is anomalous compared to the low- and moderate-resolution versions.

scholarly journals Transient Climate Response in Coupled Atmospheric–Ocean General Circulation Models

2013 ◽  
Vol 70 (4) ◽  
pp. 1291-1296 ◽  
Author(s):  
Mao-Chang Liang ◽  
Li-Ching Lin ◽  
Ka-Kit Tung ◽  
Yuk L. Yung ◽  
Shan Sun
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
General Circulation Models ◽  
Ocean Model ◽  
Climate Response ◽  
Intergovernmental Panel ◽  
Transient Climate Response ◽  
Climate System Model ◽  
Uncertainty Range ◽  
Model Version

Abstract The equilibrium climate sensitivity (ECS) has a large uncertainty range among models participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) and has recently been presented as “inherently unpredictable.” One way to circumvent this problem is to consider the transient climate response (TCR). However, the TCR among AR4 models also differs by more than a factor of 2. The authors argue that the situation may not necessarily be so pessimistic, because much of the intermodel difference may be due to the fact that the models were run with their oceans at various stages of flux adjustment with their atmosphere. This is shown by comparing multimillennium-long runs of the Goddard Institute for Space Studies model, version E, coupled with the Hybrid Coordinate Ocean Model (GISS-EH) and the Community Climate System Model, version 4 (CCSM4) with what were reported to AR4. The long model runs here reveal the range of variability (~30%) in their TCR within the same model with the same ECS. The commonly adopted remedy of subtracting the “climate drift” is ineffective and adds to the variability. The culprit is the natural variability of the control runs, which exists even at quasi equilibration. Fortunately, for simulations with multidecadal time horizon, robust solutions can be obtained by branching off thousand-year-long control runs that reach “quasi equilibration” using a new protocol, which takes advantage of the fact that forced solutions to radiative forcing forget their initial condition after 30–40 yr and instead depend mostly on the trajectory of the radiative forcing.

scholarly journals The Influence of Local Feedbacks and Northward Heat Transport on the Equilibrium Arctic Climate Response to Increased Greenhouse Gas Forcing

2012 ◽  
Vol 25 (16) ◽  
pp. 5433-5450 ◽  
Author(s):  
Jennifer E. Kay ◽  
Marika M. Holland ◽  
Cecilia M. Bitz ◽  
Edward Blanchard-Wrigglesworth ◽  
Andrew Gettelman ◽  
...  
Keyword(s):  
Heat Flux ◽  
Sea Ice ◽  
Greenhouse Gas ◽  
Heat Transport ◽  
Ocean Model ◽  
Arctic Climate ◽  
Climate Response ◽  
Surface Climate ◽  
Slab Ocean ◽  
Arctic Surface

Abstract This study uses coupled climate model experiments to identify the influence of atmospheric physics [Community Atmosphere Model, versions 4 and 5 (CAM4; CAM5)] and ocean model complexity (slab ocean, full-depth ocean) on the equilibrium Arctic climate response to an instantaneous CO2 doubling. In slab ocean model (SOM) experiments using CAM4 and CAM5, local radiative feedbacks, not atmospheric heat flux convergence, are the dominant control on the Arctic surface response to increased greenhouse gas forcing. Equilibrium Arctic surface air temperature warming and amplification are greater in the CAM5 SOM experiment than in the equivalent CAM4 SOM experiment. Larger 2 × CO2 radiative forcing, more positive Arctic surface albedo feedbacks, and less negative Arctic shortwave cloud feedbacks all contribute to greater Arctic surface warming and sea ice loss in CAM5 as compared to CAM4. When CAM4 is coupled to an active full-depth ocean model, Arctic Ocean horizontal heat flux convergence increases in response to the instantaneous CO2 doubling. Though this increased ocean northward heat transport slightly enhances Arctic sea ice extent loss, the representation of atmospheric processes (CAM4 versus CAM5) has a larger influence on the equilibrium Arctic surface climate response than the degree of ocean coupling (slab ocean versus full-depth ocean). These findings underscore that local feedbacks can be more important than northward heat transport for explaining the equilibrium Arctic surface climate response and response differences in coupled climate models. That said, the processes explaining the equilibrium climate response differences here may be different than the processes explaining intermodel spread in transient climate projections.

scholarly journals Role of AMOC in Transient Climate Response to Greenhouse Gas Forcing in Two Coupled Models

2020 ◽  
Vol 33 (14) ◽  
pp. 5845-5859
Author(s):  
Aixue Hu ◽  
Luke Van Roekel ◽  
Wilbert Weijer ◽  
Oluwayemi A. Garuba ◽  
Wei Cheng ◽  
...  
Keyword(s):  
Greenhouse Gas ◽  
Climate Sensitivity ◽  
Earth System Model ◽  
System Model ◽  
Upper Ocean ◽  
Climate Response ◽  
Earth System ◽  
Transient Climate Response ◽  
Model Version ◽  
The Mean

AbstractAs the greenhouse gas concentrations increase, a warmer climate is expected. However, numerous internal climate processes can modulate the primary radiative warming response of the climate system to rising greenhouse gas forcing. Here the particular internal climate process that we focus on is the Atlantic meridional overturning circulation (AMOC), an important global-scale feature of ocean circulation that serves to transport heat and other scalars, and we address the question of how the mean strength of AMOC can modulate the transient climate response. While the Community Earth System Model version 2 (CESM2) and the Energy Exascale Earth System Model version 1 (E3SM1) have very similar equilibrium/effective climate sensitivity, our analysis suggests that a weaker AMOC contributes in part to the higher transient climate response to a rising greenhouse gas forcing seen in E3SM1 by permitting a faster warming of the upper ocean and a concomitant slower warming of the subsurface ocean. Likewise the stronger AMOC in CESM2 by permitting a slower warming of the upper ocean leads in part to a smaller transient climate response. Thus, while the mean strength of AMOC does not affect the equilibrium/effective climate sensitivity, it is likely to play an important role in determining the transient climate response on the centennial time scale.

scholarly journals Local and Global Climate Feedbacks in Models with Differing Climate Sensitivities

2006 ◽  
Vol 19 (2) ◽  
pp. 193-209 ◽  
Author(s):  
Markus Stowasser ◽  
Kevin Hamilton ◽  
George J. Boer
Keyword(s):  
Climate Sensitivity ◽  
Positive Feedback ◽  
General Circulation ◽  
Global Climate ◽  
Tropical Pacific ◽  
Climate Feedbacks ◽  
Climate System Model ◽  
Surface Warming ◽  
Model Version ◽  
Global Mean

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.

scholarly journals The Community Climate System Model Version 3 (CCSM3)

2006 ◽  
Vol 19 (11) ◽  
pp. 2122-2143 ◽  
Author(s):  
William D. Collins ◽  
Cecilia M. Bitz ◽  
Maurice L. Blackmon ◽  
Gordon B. Bonan ◽  
Christopher S. Bretherton ◽  
...  
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Climate System ◽  
System Model ◽  
Ice Dynamics ◽  
Community Climate System Model ◽  
Climate System Model ◽  
Model Version ◽  
Systematic Biases ◽  
Community Climate

Abstract The Community Climate System Model version 3 (CCSM3) has recently been developed and released to the climate community. CCSM3 is a coupled climate model with components representing the atmosphere, ocean, sea ice, and land surface connected by a flux coupler. CCSM3 is designed to produce realistic simulations over a wide range of spatial resolutions, enabling inexpensive simulations lasting several millennia or detailed studies of continental-scale dynamics, variability, and climate change. This paper will show results from the configuration used for climate-change simulations with a T85 grid for the atmosphere and land and a grid with approximately 1° resolution for the ocean and sea ice. The new system incorporates several significant improvements in the physical parameterizations. The enhancements in the model physics are designed to reduce or eliminate several systematic biases in the mean climate produced by previous editions of CCSM. These include new treatments of cloud processes, aerosol radiative forcing, land–atmosphere fluxes, ocean mixed layer processes, and sea ice dynamics. There are significant improvements in the sea ice thickness, polar radiation budgets, tropical sea surface temperatures, and cloud radiative effects. CCSM3 can produce stable climate simulations of millennial duration without ad hoc adjustments to the fluxes exchanged among the component models. Nonetheless, there are still systematic biases in the ocean–atmosphere fluxes in coastal regions west of continents, the spectrum of ENSO variability, the spatial distribution of precipitation in the tropical oceans, and continental precipitation and surface air temperatures. Work is under way to extend CCSM to a more accurate and comprehensive model of the earth's climate system.

Equilibrium Climate Sensitivity and Transient Climate Response biased low in historical simulations of CMIP6 models

2021 ◽  
Author(s):  
Yue Dong ◽  
Kyle C. Armour ◽  
Cristian Proistosescu ◽  
Timothy Andrews ◽  
David S. Battisti ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Climate Response ◽  
Transient Climate Response ◽  
Equilibrium Climate Sensitivity
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