Recent Progress in Constraining Climate Sensitivity With Model Ensembles

Fasullo, John T.; Sanderson, Benjamin M.; Trenberth, Kevin E.

doi:10.1007/s40641-015-0021-7

Cited by 17 publications

(24 citation statements)

References 44 publications

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“…In addition, the dispersion in the ECS estimate based on the energy budget and the emergent constraint (the empirical relation found in models between the ECS and observable variable) (Fasullo et al 2015;Klein and Hall 2015) by using observation data precludes the IPCC-AR5 from providing the best estimate. These issues might be resolved at least partially by taking both ocean heat uptake and forcing efficacies into account.…”

Section: Discussionmentioning

confidence: 99%

A review of progress towards understanding the transient global mean surface temperature response to radiative perturbation

Yoshimori

Shiogama

Oka

et al. 2016

Prog. in Earth and Planet. Sci.

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The correct understanding of the transient response to external radiative perturbation is important for the interpretation of observed climate change, the prediction of near-future climate change, and committed warming under climate stabilization scenarios, as well as the estimation of equilibrium climate sensitivity based on observation data. It has been known for some time that the radiative damping rate per unit of global mean surface temperature increase varies with time, and this inconstancy affects the transient response. Knowledge of the equilibrium response alone is insufficient, but understanding the transient response of the global mean surface temperature has made rapid progress. The recent progress accompanies the relatively new concept of the efficacies of ocean heat uptake and forcing. The ocean heat uptake efficacy associates the temperature response induced by ocean heat uptake with equilibrium temperature response, and the efficacy of forcing compares the temperature response caused by non-CO 2 forcing with that by CO 2 forcing. In this review article, recent studies on these efficacies are discussed, starting from the classical global feedback framework and basis of the transient response. An attempt is made to structure different studies that emphasize different aspects of the transient response and to stress the relevance of those individual studies. The implications on the definition and computation of forcing and on the estimation of the equilibrium response in climate models are also discussed. Along with these discussions, examples are provided with MIROC climate model multi-millennial simulations.

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Section: Discussionmentioning

confidence: 99%

A review of progress towards understanding the transient global mean surface temperature response to radiative perturbation

Yoshimori

Shiogama

Oka

et al. 2016

Prog. in Earth and Planet. Sci.

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“…As a result, the CS spread can be constrained by observed LTMI into higher value among the MME (.3 K). It is physically reasonable that GCMs with stronger low-latitude LTMI should be dryer in a warming climate, resulting in a stronger positive lowcloud feedback compared with weaker-LTMI GCMs (Fasullo et al 2015;Klein and Hall 2015). However, correlation between LTMI and low-cloud feedback is not clearer than that for LTMI and CS, suggesting a remaining issue on physical consistency and effectiveness of LTMI for constraining the possible range of CS (She14; Klein and Hall 2015).…”

Section: Miroc5amentioning

confidence: 99%

“…It is essential to achieve progress in understanding of factors contributing to the spread of CS and to constrain the spread from observational metrics with physical consistency (Fasullo et al 2015;Klein and Hall 2015). Uncertainty in cloud feedback, the most important factor for the spread of CS , has been examined by decomposing into different cloud properties including regionality, height, and optical depth (e.g., Zelinka et al 2012aZelinka et al ,b, 2013hereafter Z13).…”

Section: Introductionmentioning

confidence: 99%

“…By using above different types of ensembles (particularly MME and PPE), observational metrics (called emergent constraint) associated with cloud processes were applied to constrain the uncertainty range in CS (Fasullo et al 2015;Klein and Hall 2015). Sherwood et al (2014, hereafter She14) examined a possible correspondence between CS and intensity of vertical air mixing between the boundary layer and free TABLE 1.…”

Section: Introductionmentioning

confidence: 99%

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Lower-Tropospheric Mixing as a Constraint on Cloud Feedback in a Multiparameter Multiphysics Ensemble

et al. 2016

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Factors and possible constraints to extremely large spread of effective climate sensitivity (ECS) ranging about 2.1-10.4 K are examined by using a large-member ensemble of quadrupling CO 2 experiments with an atmospheric general circulation model (AGCM). The ensemble, called the multiparameter multiphysics ensemble (MPMPE), consists of both parametric and structural uncertainties in parameterizations of cloud, cumulus convection, and turbulence based on two different versions of AGCM. The sum of the low-and middle-cloud shortwave feedback explains most of the ECS spread among the MPMPE members. For about half of the perturbed physics ensembles (PPEs) in the MPMPE, variation in lower-tropospheric mixing intensity (LTMI) corresponds well with the ECS variation, whereas it does not for the other half. In the latter PPEs, large spread in optically thick middle-cloud feedback over the equatorial ocean substantially affects the ECS, disrupting the LTMI-ECS relationship. Although observed LTMI can constrain uncertainty in the lowcloud feedback, total uncertainty of the ECS among the MPMPE cannot solely be explained by the LTMI, suggesting a limitation of single emergent constraint for the ECS.

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“…For example, Hall and Qu (2006) used the observable variation in the seasonal cycle of the snow albedo as a proxy for constraining the unobservable feedback strength to climate warming, and Cox et al (2013) and found a good correlation between the carbon cycle-climate feedback and the observable sensitivity of interannual variations in the CO 2 growth rate to temperature variations in an ensemble of models, enabling the projections to be constrained with observations. Other examples include constraints on the CO 2 fertilization effect (Wenzel et al, 2016a), equilibrium climate sensitivity and clouds (Fasullo et al, 2015;Fasullo and Trenberth, 2012;Klein and Hall, 2015;Sherwood et al, 2014), the austral jet stream , total column ozone (Karpechko et al, 2013), and sea ice (Mahlstein and Knutti, 2012;Massonnet et al, 2012). One should keep in mind, however, that the "emergent constraint" approach is based on relationships which are uncovered in models themselves.…”

Section: Current Earth System Model Evaluation Approaches and Scientimentioning

confidence: 99%

Towards improved and more routine Earth system model evaluation in CMIP

et al. 2016

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Abstract. The Coupled Model Intercomparison Project (CMIP) has successfully provided the climate community with a rich collection of simulation output from Earth system models (ESMs) that can be used to understand past climate changes and make projections and uncertainty estimates of the future. Confidence in ESMs can be gained because the models are based on physical principles and reproduce many important aspects of observed climate. More research is required to identify the processes that are most responsible for systematic biases and the magnitude and uncertainty of future projections so that more relevant performance tests can be developed. At the same time, there are many aspects of ESM evaluation that are well established and considered an essential part of systematic evaluation but have been implemented ad hoc with little community coordination. Given the diversity and complexity of ESM analysis, we argue that the CMIP community has reached a critical juncture at which many baseline aspects of model evaluation need to be performed much more efficiently and consistently. Here, we provide a perspective and viewpoint on how a more systematic, open, and rapid performance assessment of the large and diverse number of models that will participate in current and future phases of CMIP can be achieved, and announce our intention to implement such a system for CMIP6. Accomplishing this could also free up valuable resources as many scientists are frequently "re-inventing the wheel" by re-writing analysis routines for well-established analysis methods. A more systematic approach for the community would be to develop and apply evaluation tools that are based on the latest scientific knowledge and observational reference, are well suited for routine use, and provide a wide range of diagnostics and performance metrics that comprehensively characterize model behaviour as soon as the output is published to the Earth System Grid Federation (ESGF). The CMIP infrastructure enforces data standards and conventions for model output and documentation accessible via the ESGF, additionally publishing observations (obs4MIPs) and reanalyses (ana4MIPs) for modelPublished by Copernicus Publications on behalf of the European Geosciences Union. V. Eyring et al.: Towards improved and more routine Earth system model evaluation in CMIPintercomparison projects using the same data structure and organization as the ESM output. This largely facilitates routine evaluation of the ESMs, but to be able to process the data automatically alongside the ESGF, the infrastructure needs to be extended with processing capabilities at the ESGF data nodes where the evaluation tools can be executed on a routine basis. Efforts are already underway to develop community-based evaluation tools, and we encourage experts to provide additional diagnostic codes that would enhance this capability for CMIP. At the same time, we encourage the community to contribute observations and reanalyses for model evaluation to the obs4MIPs and ana4MIPs archives. The intention i...

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Recent Progress in Constraining Climate Sensitivity With Model Ensembles

Cited by 17 publications

References 44 publications

A review of progress towards understanding the transient global mean surface temperature response to radiative perturbation

A review of progress towards understanding the transient global mean surface temperature response to radiative perturbation

Lower-Tropospheric Mixing as a Constraint on Cloud Feedback in a Multiparameter Multiphysics Ensemble

Towards improved and more routine Earth system model evaluation in CMIP

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