Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere‐ocean climate models

By T. Andrews, J. Gregory, M. Webb, K. Taylor. 2012

692 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/94bdafc77d35a39c96b43be9951ed2d2e23389e8

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Citations in the corpus

Evaluating process-based integrated assessment models of climate change mitigation (2017, background): “Cloud feedbacks represent the main cause of variation between models in this aggregate diagnostic indicator (100).”
Ocean heat uptake and its consequences for the magnitude of sea level rise and climate change (2012, methodology): “:3) is obtained from experiments in which CO 2 is instantaneously increased and then held constant [ Andrews et al. , 2012] (Table 1 in Text S1).”
The Dependence of Global Cloud and Lapse Rate Feedbacks on the Spatial Structure of Tropical Pacific Warming (2018, methodology): “In addition, HadGEM2 has a mineral dust scheme that has been shown to give rise to changes in atmospheric dust load and top-of-theatmosphere radiation under climate change (e.g., Andrews et al. 2012b), which would be aliased into the residual here.”
On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates (2013, background): “Actually, the differences between Andrews et al (2012)’s estimates381 and ours remain within ±5% for 7 models that are analyzed in both studies, while one model only (INMCM4)382 exhibits a larger difference between the two methodologies (9.5% difference).”
The challenge of simulating the warmth of the mid-Miocene climatic optimum in CESM1 (2013, methodology): “…Krapp and Jungclaus, 2011), matching proxy records at the MMCO is challenging even in the latest generation of models and using a model with a climate sensitivity near the median of Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) estimates (Andrews et al., 2012).”
Causes of Higher Climate Sensitivity in CMIP6 Models (2020, methodology): “Relatedly, ERF2× estimated via equation (1) is subject to substantial uncertainties (Andrews et al., 2012; Chung & Soden, 2015).”
Anthropogenic and Natural Radiative Forcing (2014, methodology): “Despite the low bias in fixed-SST ERF due to land responses, results from a multi-model analysis of the forcing due to CO2 are 7% greater using this method than using the regression technique (Andrews et al., 2012a) though this is within the uncertainty range of the calculations.”
The ocean’s role in the transient response of climate to abrupt greenhouse gas forcing (2015, methodology): “1 Wm K global radiative feedback found in the ensemble of CMIP5 models (Andrews et al. 2012), and smaller still than the radiative feedbacks over the ocean that tend to damp more strongly than those over the land (Armour et al.”
The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6. (2016, methodology): “…for the first time in the multi-model context (Kamae and Watanabe, 2012; Ringer at al., 2014; Kamae et al., 2015) in conjunction with the CMIP5 sstClim/sstClim4xCO2 experiments which were based on climatological pre-industrial SSTs (Andrews et al., 2012; Zelinka et al., 2013; Vial et al., 2013).”
Developments in the MPI‐M Earth System Model version 1.2 (MPI‐ESM1.2) and Its Response to Increasing CO2 (2019, methodology): “…common to measure ECS by instantaneously quadrupling CO 2 in a coupled model run for 150 years (abrupt4xCO2) and then using linear regression between radiation imbalance and global mean surface temperature to estimate the long-term warming response (Andrews et al., 2012; Gregory et al., 2004).”
Emergent constraints on equilibrium climate sensitivity in CMIP5: do they hold for CMIP6? (2020, methodology): “In this calculation, the linear fit of a corresponding pre-industrial control run is subtracted from the 4xCO 2 run to remove any model drift that is present in the control climate without adding noise (Andrews et al., 2012).”
Evolution of the Global Coupled Climate Response to Arctic Sea Ice Loss during 1990–2090 and Its Contribution to Climate Change (2018, background): “…of climate change responses among models might reflect different balances in the ‘‘tug of war’’ between tropical warming and Arctic warming (e.g., Barnes and Polvani 2015; Deser et al. 2015; Blackport and Kushner 2017; McCusker et al. 2017; Oudar et al. 2017) or differences in the…”