An Assessment of the Primary Sources of Spread of Global Warming Estimates from Coupled Atmosphere–Ocean Models

By J. Dufresne, Sandrine Bony. 2008

438 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/f28bd82538c4cc6af7df2e06f9196b9506f9912f

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Citations in the corpus

Presentation and Evaluation of the IPSL‐CM6A‐LR Climate Model (2020, methodology): “The relative contributions to ECS are calculated following Dufresne and Bony (2008) and Vial et al. (2013) and illustrated in the bar plots.”
Simulation of Present-Day and Twenty-First-Century Energy Budgets of the Southern Oceans (2010, background): “Bony et al. (2004; 2006) and Dufresne and Bony (2008) conclude that the main source of model differences remains cloud feedback, and especially from low-level clouds and in regions of subsidence.”
Evaluating Emergent Constraints on Equilibrium Climate Sensitivity (2018, methodology): “Because l Cld dominates intermodel spread in ECS (Dufresne and Bony 2008; Caldwell et al. 2016), it receives by far the largest weighting in Table 3.”
The EarthCARE Satellite: The Next Step Forward in Global Measurements of Clouds, Aerosols, Precipitation, and Radiation (2015, background): “More details on the technical specifications of ATLID can be found in Durand et al. (2007).”
High sensitivity of future global warming to land carbon cycle processes (2012, background): “this has mainly focused on physical climate feedbacks [6–9] through variables such as the climate sensitivity (CS) [10] or the transient climate response (TCR) [6, 11] or considered emergent constraints arising from limiting total emissions of CO2 within simpler modelling frameworks [12–14].”
The vertical distribution of cloud feedback in coupled ocean‐atmosphere models (2011, neutral): “Lett., 38, L12704, doi:10.1029/2011GL047632.”
Transient Climate Response in a Two-Layer Energy-Balance Model. Part I: Analytical Solution and Parameter Calibration Using CMIP5 AOGCM Experiments (2013, methodology): “They are useful to summarize AOGCM global thermal properties and to compare and analyze AOGCM responses (Raper et al. 2002; Soden and Held 2006; Gregory and Forster 2008; Dufresne and Bony 2008).”
On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates (2013, methodology): “…Project (CMIP3),43 cloud feedbacks were identified as the leading source of spread of climate sensitivity estimates (Bony et al, 2006;44 Dufresne and Bony, 2008; Soden and Held, 2006), with a major contribution from low-cloud feedbacks (Bony and45 Dufresne, 2005; Randall et al, 2007;…”
Origins of differences in climate sensitivity, forcing and feedback in climate models (2013, methodology): “…twice as much to the range in effective climate sensitivity as differences in effective CO2 forcings, qualitatively consistent with the findings of earlier studies which did not allow for the effects of rapid cloud adjustments on radiative forcing (e.g. Webb et al. 2006; Dufresne and Bony 2008).”
A new statistical approach to climate change detection and attribution (2016, background): “In contrast, the cloud feedback, which is the most uncertain feedback in 1 3 the response to increasing GHGs (Dufresne and Bony 2008), is highly variable over space, and able to induce local and regional changes in the atmospheric circulation (Stevens and Bony 2013), that could contribute substantia”