A review of progress towards understanding the transient global mean surface temperature response to radiative perturbation

Abstract

The correct understanding of the transient response to external radiative perturbation is important for the interpretation of observed climate change, the prediction of near-future climate change, and committed warming under climate stabilization scenarios, as well as the estimation of equilibrium climate sensitivity based on observation data. It has been known for some time that the radiative damping rate per unit of global mean surface temperature increase varies with time, and this inconstancy affects the transient response. Knowledge of the equilibrium response alone is insufficient, but understanding the transient response of the global mean surface temperature has made rapid progress. The recent progress accompanies the relatively new concept of the efficacies of ocean heat uptake and forcing. The ocean heat uptake efficacy associates the temperature response induced by ocean heat uptake with equilibrium temperature response, and the efficacy of forcing compares the temperature response caused by non-CO 2 forcing with that by CO 2 forcing. In this review article, recent studies on these efficacies are discussed, starting from the classical global feedback framework and basis of the transient response. An attempt is made to structure different studies that emphasize different aspects of the transient response and to stress the relevance of those individual studies. The implications on the definition and computation of forcing and on the estimation of the equilibrium response in climate models are also discussed. Along with these discussions, examples are provided with MIROC climate model multi-millennial simulations.

The post‐2002 global surface warming slowdown caused by the subtropical Southern Ocean heating acceleration

“…Our method is based on two energy budget equations. The first one is energy budget at the top of the atmosphere (TOA) which is widely used in climate sensitivity studies [ Knutti and Hegerl , ; Yoshimori et al ., ]: where N is TOA net radiation input, F is forcing, T is surface temperature, Λ is a feedback parameter, and Δ indicates an anomaly [ Hansen and Takahashi , ; Yoshimori et al ., ]. The second one is the energy conservation of the Earth; the TOA excess energy needs to be used for an increase in the ocean heat content and/or changes in energy except the ocean such as melting of glaciers/sea ice and land/atmosphere warming: where E O and E EO represent ocean heat content and nonocean total energy (i.e., heat stored except the ocean) per unit area of Earth's surface, respectively.…”

“…Our method is based on two energy budget equations. The first one is energy budget at the top of the atmosphere (TOA) which is widely used in climate sensitivity studies [Knutti and Hegerl, 2008;Yoshimori et al, 2016]:…”

Responses of Basal Melting of Antarctic Ice Shelves to the Climatic Forcing of the Last Glacial Maximum and CO2 Doubling

“…The LGM experiment followed the protocol of PMIP2 (Braconnot et al 2007) in which greenhouse gas concentrations (CO 2 value of 185 ppm) and global LGM ice sheet topography were prescribed (Kawamura et al 2017). In the 23CO 2 experiment, we increased the atmospheric CO 2 concentration by 1% compound per year from the preindustrial value (285 ppm) until it doubled (571 ppm, at the 70th year) and the value was held constant thereafter (Yamamoto et al 2015;Yoshimori et al 2016). Based on the representative concentration pathway (RCP), CO 2 concentration reaches a value of 538 ppm at 2100 for RCP 4.5 and 571 ppm at mid-2050 for RCP 8.5.…”

“…We use an AOGCM and a circumpolar ocean model that resolves ice shelf cavity circulations to investigate the response of the basal melt rate of the Antarctic ice shelf. We simulate the climates of the LGM and a quasi-equilibrium CO 2 doubling (23CO 2 ) as representatives of extreme colder and warmer conditions, respectively, which are often referred to as benchmarks among paleoclimate modeling studies and future projections (Braconnot et al 2007;Yoshimori et al 2009). A challenge in simulating the Antarctic ice sheet at the LGM is that both the climatic conditions and the Antarctic ice shelf configuration affect the basal melt rate, as simulated by Kusahara et al (2015) using the same circumpolar ocean model driven by the same AOGCM as here.…”

Recent progress toward reducing the uncertainty in tropical low cloud feedback and climate sensitivity: a review

“…While climate scientists are devoted to the development of realistic and reliable climate models, the uncertainty range of the modeled ECS has not been reduced efficiently since the Charney report (Charney et al 1979) published in 1979 (Maslin and Austin 2012). The state-of-the-art estimates of ECS and transient climate response (TCR; a response of global-mean SAT to a gradually increasing atmospheric CO 2 concentration) from historical observations also have substantial uncertainty (e.g., Flato et al 2014) due to difficulty in accurate estimations of ocean heat uptake and forcing (e.g., Yoshimori et al 2016). Inter-model spread in feedback between the cloud and the top of the atmosphere (TOA) radiation, particularly shortwave reflectance due to cloud in the tropics, has been suggested to be the major factor for the uncertainty in ECS (e.g., Cess et al 1990;Dufresne and Bony 2008;Boucher et al 2014;Caldwell et al 2016).…”