Origins of differences in climate sensitivity, forcing and feedback in climate models

By M. Webb, F. H. Lambert, J. Gregory. Climate Dynamics, 2013

213 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/b265b46e67f5a8bab49b39668a3e0863bd80a1df

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

In Global and Planetary Change

Citations in the corpus

Emergent Constraints for Cloud Feedbacks (2015, unknown): “This predictand depends on a number of mostly independent feedbacks (and forcing), and each of these contributes to intermodel variance [50].”
Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High‐Resolution Simulations (2017, background): “Parameterizations of clouds dominate the uncertainties in physical processes [Cess et al., 1989, 1990; Stephens, 2005; Bony et al., 2006; Soden and Held, 2006; Vial et al., 2013; Webb et al., 2013; Brient and Schneider, 2016].”
Causes of Higher Climate Sensitivity in CMIP6 Models (2020, result): “3 of 12 Dufresne & Bony, 2008; Soden & Held, 2006; Webb et al., 2013), the cloud feedback exhibits the largest intermodel spread of all feedbacks and is highly correlated with ECS in both collections (Figure S4A).”
Time-Varying Climate Sensitivity from Regional Feedbacks (2012, methodology): “This method has been widely applied to estimate feedbacks and forcing within both models and observations (Forster and Taylor 2006; Forster and Gregory 2006; Gregory and Webb 2008; Andrews and Forster 2008; Williams et al. 2008; Murphy et al. 2009; Boer 2011; Crook et al. 2011; Andrews et al. 2012a;”
Mechanisms of marine low cloud sensitivity to idealized climate perturbations: A single‐LES exploration extending the CGILS cases (2013, methodology): “[30] As discussed by Wood and Bretherton [2006], EIS is a refinement of LTS, which assumes the LTS is composed of an inversion jump (the EIS) and moist-adiabatic temperature stratification between a nominal LCL and 700 hPa.”
The Dependence of Global Cloud and Lapse Rate Feedbacks on the Spatial Structure of Tropical Pacific Warming (2018, methodology): “…variations in lapse rate feedback are also determined by the structure of surface temperature change 2Qu et al. (2014, 2015b) actually use the estimated inversion strength (EIS) of Wood and Bretherton (2006) rather than LTS, but EIS and LTS have a similar characteristic response (Webb et al. 2013).”
Uncertainty in Model Climate Sensitivity Traced to Representations of Cumulus Precipitation Microphysics (2016, background): “…Bony et al. 2004; Bony and Dufresne 2005; Bony et al. 2006; Stephens 2005; Wyant et al. 2006; Webb et al. 2006; Soden and Held 2006; Dufresne and Bony 2008; Webb et al. 2013; Zelinka et al. 2013; Zhang et al. 2013; Sherwood et al. 2014; Bretherton et al. 2014; Webb et al. 2015; Bretherton 2015).”
Contributions of Different Cloud Types to Feedbacks and Rapid Adjustments in CMIP5 (2012, background): “The difference map between cloud-induced OLR anomalies and LWCRE anomalies (Figure 8c) exhibits relatively uniform positive values that closely tracks the mean state high cloud distribution (see also Figure 1 of Wyant et al. (2012)). This difference map provides an estimate of the so-called cloud ma”
Observational Evidence That Enhanced Subsidence Reduces Subtropical Marine Boundary Layer Cloudiness (2013, background): “For the monthly data on which our study is based, ignoring horizontal advection is reasonable (Wood and Bretherton 2004; Wang et al. 2011).”
Low-Cloud Feedbacks from Cloud-Controlling Factors: A Review (2017, background): “contribution results from the facts that (1) climate models universally predict, with robust physical justification, that EIS will increase with warming (Webb et al. 2013; Qu et al. 2015a), and (2) cloud amount and the associated reflection of solar radiation increases strongly with increases in EIS”
Mixed‐phase cloud physics and Southern Ocean cloud feedback in climate models (2015, background): “Increasing stability is a robust feature across GCMs, although the relationship between cloud fraction and stability varies significantly among models [Caldwell et al., 2013; Qu et al., 2014; Webb et al., 2013].”