Spatial Patterns of Modeled Climate Feedback and Contributions to Temperature Response and Polar Amplification

Abstract

Spatial patterns of local climate feedback and equilibrium partial temperature responses are produced from eight general circulation models with slab oceans forced by doubling carbon dioxide (CO2). The analysis is extended to other forcing mechanisms with the Met Office Hadley Centre slab ocean climate model version 3 (HadSM3). In agreement with previous studies, the greatest intermodel differences are in the tropical cloud feedbacks. However, the greatest intermodel spread in the equilibrium temperature response comes from the water vapor plus lapse rate feedback, not clouds, disagreeing with a previous study. Although the surface albedo feedback contributes most in the annual mean to the greater warming of high latitudes, compared to the tropics (polar amplification), its effect is significantly ameliorated by shortwave cloud feedback. In different seasons the relative importance of the contributions varies considerably, with longwave cloudy-sky feedback and horizontal heat transport plus ocean heat release playing a major role during winter and autumn when polar amplification is greatest. The greatest intermodel spread in annual mean polar amplification is due to variations in horizontal heat transport and shortwave cloud feedback. Spatial patterns of local climate feedback for HadSM3 forced with 2 × CO2, +2% solar, low-level scattering aerosol and high-level absorbing aerosol are more similar than those for different models forced with 2 × CO2. However, the equilibrium temperature response to high-level absorbing aerosol shows considerably enhanced polar amplification compared to the other forcing mechanisms, largely due to differences in horizontal heat transport and water vapor plus lapse rate feedback, with the forcing itself acting to reduce amplification. Such variations in high-latitude response between models and forcing mechanisms make it difficult to infer specific causes of recent Arctic temperature change.

Advances in understanding and parameterization of small-scale physical processes in the marine Arctic climate system: a review

“…The cloud fraction has an annual cycle with a maximum in early autumn and minimum during late winter (e.g. Curry et al, 1996;Shupe et al, 2011). This has been observed since the beginning of the satellite era , yet atmospheric models continue to struggle with even this first-order cloud property.…”

“…Cloud top radiative cooling is typically very efficient as near-adiabatic liquid water content (LWC) profiles are common in the Arctic (Curry, 1986;Shupe et al, 2008). Arctic MPS droplet radii generally also increase with height (e.g.…”

“…Several recent studies have stressed the close connections between these processes. The surface albedo feedback (SAF) mechanism is reputed to have been an important contributor to the loss of Arctic sea ice over the last few decades (Screen and Simmonds, 2010b;Crook et al, 2011;Taylor et al, 2013). By synthesizing a variety of remote sensing and field measurements, both Flanner et al (2011) and Hudson (2011) concluded that the change in the radiative impact of the Arctic sea ice at the top of the atmosphere in the period 1979-2008 has been a reduced cooling of about 0.1 Wm −2 .…”

Climate feedback efficiency and synergy

“…An advantage of diagnostic methods is that they can be applied across models after they have been run according to a specified protocol facilitated by large model intercomparison projects. Frequently, such intercomparison studies find that the major contributor to uncertainty in climate sensitivity is cloud feedbacks (Cess et al 1990;Colman 2003;Soden and Held 2006;Dufresne and Bony 2008;Soden et al 2008;Vial et al 2013;Webb et al 2013), while some studies find less pronounced cross-model variability in the cloud feedback (Gregory and Webb 2008;Crook et al 2011).…”

Robust Seasonality of Arctic Warming Processes in Two Different Versions of the MIROC GCM

“…This approach is particularly useful for multimodel analysis in which available data are limited and additional experiments may not be coordinated easily (Crook et al 2011;Lu and Cai 2009a). It was shown that the effect of longwave radiation associated with the change in atmospheric temperature profile is one of the dominant terms in the Arctic (Yoshimori et al 2009).…”