On dynamic and thermodynamic components of cloud changes

By Sandrine Bony, J. Dufresne, H. Treut, J. Morcrette, C. Senior. 2004

463 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/6e70c1d9f4076f230bbf33c928d7b1352546e897

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Citations in the corpus

A quantitative performance assessment of cloud regimes in climate models (2009, background): “Bony et al. 2004; Williams et al. 2006; Norris and Weaver 2001; Tselioudis et al. 2000).”
Changes in the convective population and thermodynamic environments in convection-permitting regional climate simulations over the United States (2017, background): “However, despite the importance of clouds on the hydrological cycle and energy budget of the Earth, it is well recognized that climate models produce cloud radiative feedbacks that are notably different between models that sometimes have the opposite sign (Le Treut and McAvaney 2000; Bony et al. 200”
Presentation and Evaluation of the IPSL‐CM6A‐LR Climate Model (2020, background): “This framework introduced by Bony et al. (2004) allows for attribution of changes in a climate variable to a given tropical circulation regime, ranging from strong ascent to strong subsidence regimes with increasing ω500 values.”
Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI) (2011, background): “Model information Organization Model* Type Horizontal resolution Vertical levels Model reference BMRC (Aus) BAM 4.0.21 Global T63 60 Zhong et al. (2001) CCC (Can) CCCma Global T47 35 von Salzen et al. (2005) CMC (Can) GEM Regional 0.58 3 0.58 53 Côté et al. (1998) CSU (US) BUGS Global 2.58 3 2.58 ”
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.”
Tropical climate described as a distribution of weather states indicated by distinct mesoscale cloud property mixtures (2005, background): “divergent component of the circulation that the consequent weather analyses (and reanalyses) of the circulation are much more sensitive to model parameterizations (but see Del Genio and Kovari [2002] and Bony et al. [2004]).”
On Constraining Estimates of Climate Sensitivity with Present-Day Observations through Model Weighting (2011, background): “0), so we sort present-day CRESW by this quantity (Bony et al. 2004).”
Connections Between Clouds, Radiation, and Midlatitude Dynamics: a Review (2015, background): “Thus, while the dynamical component of the cloud feedback can be a first-order term on a regional scale, particularly in the tropics [4], in a zonal- and annual-mean sense, the thermodynamic component appears to be dominant around the midlatitudes.”
Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part I: Cloud Radiative Kernels (2012, methodology): “0) models did not archive specific humidity and/or temperature, making it impossible to compute cloud feedbacks from the adjusted change in cloud radiative forcing of Shell et al. (2008) and Soden et al. (2008). For the models in which it is possible to calculate the adjusted change in cloud radiati”
Comparing clouds and their seasonal variations in 10 atmospheric general circulation models with satellite measurements (2005, background): “Even though our results do not invalidate cloud feedbacks and climate sensitivity results from the models, the fact that cloud feedback uncertainties have not been reduced appreciably in the last 15 years [Cubasch et al., 2001; Bony et al., 2004] suggests the need to improve the”
Present-day climate and climate sensitivity in the meteorological research institute coupled GCM version 2.3 (MRI-CGCM2.3) (2006, methodology): “We conducted analyses similar to Bony et al. (2004), who discretized cloud forcing into circulation regimes, defined by large-scale vertical velocity at 500 hPa, to unravel the dynamic and thermodynamic components of cloud changes.”
Cloud feedback mechanisms and their representation in global climate models (2017, unknown): “This poses a particular challenge: not only are the cloud responses to a given dynamical forcing uncertain 141 , but the future dynamical response is also much more poorly constrained than the thermodynamic one 142 .”
How reliable are climate models? (2007, background): “…of model-simulated climate changes, detailed process-level comparisons of, for example, simulated and observed cloud behaviour may be even more important, since they give more direct information on the functioning of the subgrid scale parametrizations in the models (e.g. Bony et al., 2004).”