Climate Feedbacks in CCSM3 under Changing CO2 Forcing. Part II: Variation of Climate Feedbacks and Sensitivity with Forcing

Abstract

Are equilibrium climate sensitivity and the associated radiative feedbacks a constant property of the climate system, or do they change with forcing magnitude and base climate? Using the radiative kernel technique, feedbacks and climate sensitivity are evaluated in a fully coupled general circulation model (GCM) for three successive doublings of carbon dioxide starting from present-day concentrations. Climate sensitivity increases by 23% between the first and third CO 2 doublings. Increases in the positive water vapor and cloud feedbacks are partially balanced by a decrease in the positive surface albedo feedback and an increase in the negative lapse rate feedback. Feedbacks can be decomposed into a radiative flux change and a climate variable response to temperature change. The changes in water vapor and Planck feedbacks are due largely to changes in the radiative response with climate state. Higher concentrations of greenhouse gases and higher temperatures lead to more absorption and emission of longwave radiation. Changes in cloud feedbacks are dominated by the climate response to temperature change, while the lapse rate and albedo feedbacks combine elements of both. Simulations with a slab ocean model (SOM) version of the GCM are used to verify whether an SOM-GCM accurately reproduces the behavior of the fully coupled model. Although feedbacks differ in magnitude between model configurations (with differences as large as those between CO 2 doublings for some feedbacks), changes in feedbacks between CO 2 doublings are consistent in sign and magnitude in the SOM-GCM and the fully coupled model.

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

“…Meraner et al (2013) argued another aspect of inconstancy of the global feedback parameter, in which the parameter becomes less positive and hence the ECS becomes larger in a warmer climate through enhanced water vapor feedback. The state dependency of climate feedbacks has been discussed in many previous studies (e.g., Colman and McAvaney 2009;Colman et al 1997;Feldl and Roe 2013;Hansen et al 2005;Jonko et al 2013;Yoshimori et al 2011), but the result appears to depend on the model and so the effect of the dependency on the transient response still needs to be established. In a similar context, the possibility of inconstancy of the climate resistance parameter (as well as the global feedback parameter) in the CMIP5 AOGCMs was reported by Gregory et al (2015), although they also listed errors in the estimated radiative forcing as an alternate or additional possibility.…”

nonlinMIP contribution to CMIP6: model intercomparison project for non-linear mechanisms: physical basis, experimental design and analysis principles (v1.0)

“…3.2). Some examples have been known for some time, such as changing feedbacks through retreating snow/sea ice or increasing water vapour (Hansen et al, 2005;Colman and McAvaney, 2009;Jonko et al, 2013;Meraner et al, 2013). Some palaeoclimate evidence supports the idea that climate sensitivity increases with warming (Caballero and Huber, 2013;Shaffer et al, 2016), which is important for the risk of high-end global warming (Bloch-Johnson et al, 2015).…”

Forcing and feedback in the MPI‐ESM‐LR coupled model under abruptly quadrupled CO2

“…Sea ice for instance is initially bounded by the continents [Eisenman et al, 2011] and may eventually disappear altogether, thereby inducing a nonlinear feedback. Also, cloud and water vapor feedbacks could potentially strengthen in warmer climates [Abbot et al, 2009;Jonko et al, 2013]. Furthermore, some models do indicate increasing forcing from a doubling of CO 2 in warmer climates [Hansen et al, 2005;Colman and McAvaney, 2009].…”

“…Under this assumption, we find instead that water vapor feedback increases, and surface albedo feedback decreases, while temperature and cloud feedback make the total feedback more positive, regardless of the choice of kernels. The changes in the individual feedbacks could be compared to those computed by Jonko et al [2013], who also used the kernel technique to evaluate the change in feedbacks for three successive CO 2 doublings in a fully coupled general circulation model. In agreement with our results, they also find a slightly decreasing temperature feedback and an increasing cloud feedback for their first two CO 2 doublings from preindustrial levels.…”