On the Use of Cloud Forcing to Estimate Cloud Feedback

By Brian J. Soden, A. Broccoli, Richard S. Hemler. 2004

261 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/6cbf7118dbc9e99f79b3028e56aa93469c3339d4

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Citations in the corpus

CGILS: Results from the first phase of an international project to understand the physical mechanisms of low cloud feedbacks in single column models (2013, methodology): “ECHAM6 (ECMWFUniversity of Hamburg Model Version 6) Max-Planck Institute of Meteorology, Germany Stevens et al. [2013] Suvarchal Cheedela and Bjorn Stevens 31/9”
Cloud Feedbacks in the Climate System: A Critical Review (2005, methodology): “Soden et al. (2004) refer to the latter method as the partial radiative perturbation method, which typically considers the TOA budget in the form RTOA R X1 Ts , X2 Ts , . . . , Xn Ts ; Ts , where X1,...,n(Ts) represent the physical processes that connect a given variable such as cloud type and…”
How Well Do We Understand and Evaluate Climate Change Feedback Processes (2006, methodology): “As discussed by Zhang et al. (1996), Colman (2003), and Soden et al. (2004), the magnitude (and sometimes the sign) of the cloud feedback parameter diagnosed by this method differs from that diagnosed by the PRP approach.”
Seasonality of polar surface warming amplification in climate simulations (2009, background): “feedbacks are also included in the change of the CRF, Soden et al. [2004] highlighted the need to interpret the change in the CRF properly.”
A comparison of low-latitude cloud properties and their response to climate change in three AGCMs sorted into regimes using mid-tropospheric vertical velocity (2006, methodology): “Note that changes in cloud forcing are related to but not the same as cloud feedbacks (e.g., Soden et al. 2004).”
Forcing and feedback in the MPI‐ESM‐LR coupled model under abruptly quadrupled CO2 (2013, background): “Nevertheless, this approach can be misleading because DCRE depends not only on changes in the cloud field but also on changes in the environment [Colman, 2003; Soden et al., 2004].”
On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles (2006, methodology): “This is an example of the cloud masking effect discussed by Colman (2003) and Soden et al. (2004) .”
Why is longwave cloud feedback positive (2010, methodology): “From DLWCF to LW Cloud Feedback: Applying the Radiative Kernels [45] The change in LWCF is not equal to the LW cloud feedback, though they are correlated [Soden et al., 2004; Soden and Held, 2006].”
On Constraining Estimates of Climate Sensitivity with Present-Day Observations through Model Weighting (2011, background): “Climate models produce a range of estimates of climate sensitivity which can themselves be sensitive to fairly small changes in model formulation (Soden et al. 2004).”
A quantitative performance assessment of cloud regimes in climate models (2009, background): “This is seen in stratocumulus over ice and snow covered regions, and changes in the regime histograms (ESM 10) reveal that at least some of the response is an actual change in regime s rather than an artifact of cloud masking over ice/snow (e.g. Soden et al. 2004 ).”
On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates (2013, background): “…owing to cloud-masking effects, the sign of ∆CRE can differ from that of the cloud feedback (a571 negative ∆CRE being generally associated with a neutral or weakly positive cloud feedback) and that both572 measures differ by an offset of about 0.3 Wm−2K−1 (Soden and Held, 2006; Soden et al, 2004).”
The Climate Sensitivity and Its Components Diagnosed from Earth Radiation Budget Data (2005, background): “As a result of cloud masking of the noncloud feedback terms, feedbacks analyzed using cloud radiative forcing will be systematically different than those from partial radiative perturbations (Soden et al. 2004).”
An Assessment of Climate Feedbacks in Coupled Ocean–Atmosphere Models (2006, methodology): “…of feedback assessment aliases noncloud feedbacks into the cloud-forcing term; thus, scatter in the cloud-forcing response can partially result from differences in the total-sky components of the other feedback variables (Zhang et al. 1994; Colman and McAvaney 1997; Colman 2003; Soden et al. 2004).”
Evaluating Emergent Constraints on Equilibrium Climate Sensitivity (2018, methodology): “…F and net feedback values l using the equilibrated top-of-atmosphere (TOA) response to a radiative forcing perturbation: Cloud feedbacks in the tables used for CMIP3 and CMIP5 models were computed using the adjusted cloud radiative forcing technique (Soden et al. 2004, 2008; Shell et al. 2008).”
Estimating shortwave radiative forcing and response in climate models (2007, methodology): “Winton (2005) developed several methods for estimating surface albedo feedback based on monthly mean model output.”