Observational constraints on mixed-phase clouds imply higher climate sensitivity

Abstract

Global climate model (GCM) estimates of the equilibrium global mean surface temperature response to a doubling of atmospheric CO2, measured by the equilibrium climate sensitivity (ECS), range from 2.0° to 4.6°C. Clouds are among the leading causes of this uncertainty. Here we show that the ECS can be up to 1.3°C higher in simulations where mixed-phase clouds consisting of ice crystals and supercooled liquid droplets are constrained by global satellite observations. The higher ECS estimates are directly linked to a weakened cloud-phase feedback arising from a decreased cloud glaciation rate in a warmer climate. We point out the need for realistic representations of the supercooled liquid fraction in mixed-phase clouds in GCMs, given the sensitivity of the ECS to the cloud-phase feedback.

The importance of mixed-phase clouds for climate sensitivity in the global aerosol-climate model ECHAM6-HAM2

“…ECS ranges between 1.8 and 2.8 K in all our simulations ( Table 3) and with that lies on the lower side of the range of ECS estimated in the last IPCC report (Collins et al, 5 2013;Flato et al, 2013) and from CMIP5 models . Similar to Tan et al (2016), ECS increases by ∼ 30% when increasing SLF from almost zero to one (simulations ALL_ICE and ALL_LIQ in this paper vs. Low-SLF and High-SLF in Tan et al (2016) Figure 4. Effective radiative forcing due to aerosol-radiation and aerosol-cloud interactions (ERFari+aci) and equilibrium climate sensitivity for the various sensitivity simulations described in Table 1. low SLF.…”

“…Since in ECHAM6-HAM2 this is only the case in simulation ALL_ICE, this is the only simulation with a distinctively lower ECS. In CAM5, too much shortwave radiation is absorbed over the Southern Ocean in their present-day climate (Kay et al, 2016), which explains why ECS is also sensitive to an increase in SLF in the study by Tan et al (2016).…”

“…• C (simulation ALL_LIQ) similar to what has been done in Tan et al (2016) and Lohmann (2002). Another aspect to the possible impact of ice on ERFari+aci is the nucleation in cirrus clouds.…”

“…If mixed-phase clouds in the current climate contain too few supercooled cloud 5 droplets, too much ice will change to liquid water in a warmer climate. As shown by Tan et al (2016), this overestimates the negative cloud phase feedback and underestimates ECS in the CAM global climate model (GCM). Here we are using the newest version of the ECHAM6-HAM2 GCM to investigate the importance of mixed-phase clouds for ECS.…”

The “Grey Zone” cold air outbreak global model intercomparison: A cross evaluation using large‐eddy simulations

“…Many of the major biases in global climate models are related to processes that are central in cold air outbreaks, such as vertical mixing in the boundary layer and mixed-phase cloud microphysics [Tsushima et al, 2006;Gettelman et al, 2010;Pithan et al, 2014;Tan et al, 2016].…”