ABSTRACT
Clouds are important factors when projecting future climate. Unfortunately, future cloud fractional cover (the portion of the sky covered by clouds) is associated with significant uncertainty, making climate projections difficult. In this paper, we present the European Cloud Cover dataset, which can be used to learn statistical relations between cloud cover and other environmental variables, to potentially improve future climate projections. The dataset was created using a novel technique called Area Weighting Regridding Scheme to map satellite observations to cloud fractional cover on the same grid as the other variables in the dataset. Baseline experiments using autoregressive models document that it is possible to use the dataset to predict cloud fractional cover.
ABSTRACT
Black carbon (BC) aerosols from incomplete combustion generally warm the climate, but the magnitudes of their various interactions with climate are still uncertain. A key knowledge gap is their role as ice nucleating particles (INPs), enabling ice formation in clouds. Here we assess the global radiative impacts of BC acting as INPs, using simulations with the Community Earth System Model 2 climate model updated to include new laboratory-based ice nucleation parameterizations. Overall, we find a moderate cooling through changes to stratiform cirrus clouds, counteracting the well-known net warming from BC's direct scattering and absorption of radiation. Our best estimates indicate that BC INPs generally thin cirrus by indirectly inhibiting the freezing of solution aerosol, with a global net radiative impact of -0.13 ± 0.07 W/m2. Sensitivity tests of BC amounts and ice nucleating efficiencies, and uncertainties in the environment where ice crystals form, show a potential range of impacts from -0.30 to +0.02 W/m2.
ABSTRACT
Aerosol emissions from forest fires may impact cloud droplet activation through an increase in particle number concentrations ("the number effect") and also through a decrease in the hygroscopicity κ of the entire aerosol population ("the hygroscopicity effect") when fully internal mixing is assumed in models. This study investigated these effects of fire particles on the properties of simulated deep convective clouds (DCCs), using cloud-resolving simulations with the Weather Research and Forecasting model coupled with Chemistry for a case study in a partly idealized setting. We found that the magnitude of the hygroscopicity effect was in some cases strong enough to entirely offset the number/size effect, in terms of its influence on modeled droplet and ice crystal concentrations. More specifically, in the case studied here, the droplet number concentration was reduced by about 37% or more due solely to the hygroscopicity effect. In the atmosphere, by contrast, fire particles likely have a much weaker impact on the hygroscopicity of the pre-existing background aerosol, as such a strong impact would occur only if the fire particles mixed immediately and uniformly with the background. We also show that the differences in the number of activated droplets eventually led to differences in the optical thickness of the clouds aloft, though this finding is limited to only a few hours of the initial development stage of the DCCs. These results suggest that accurately and rigorously representing aerosol mixing and κ in models is an important step toward accurately simulating aerosol-cloud interactions under the influence of fires.
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.
ABSTRACT
Theoretical models have been used to argue that seasonal mean monsoons will shift abruptly and discontinuously from wet to dry stable states as their radiative forcings pass a critical threshold, sometimes referred to as a "tipping point." Further support for a strongly nonlinear response of monsoons to radiative forcings is found in the seasonal onset of the South Asian summer monsoon, which is abrupt compared with the annual cycle of insolation. Here it is shown that the seasonal mean strength of monsoons instead exhibits a nearly linear dependence on a wide range of radiative forcings. First, a previous theory that predicted a discontinuous, threshold response is shown to omit a dominant stabilizing term in the equations of motion; a corrected theory predicts a continuous and nearly linear response of seasonal mean monsoon strength to forcings. A comprehensive global climate model is then used to show that the seasonal mean South Asian monsoon exhibits a near-linear dependence on a wide range of isolated greenhouse gas, aerosol, and surface albedo forcings. This model reproduces the observed abrupt seasonal onset of the South Asian monsoon but produces a near-linear response of the mean monsoon by changing the duration of the summer circulation and the latitude of that circulation's ascent branch. Thus, neither a physically correct theoretical model nor a comprehensive climate model support the idea that seasonal mean monsoons will undergo abrupt, nonlinear shifts in response to changes in greenhouse gas concentrations, aerosol emissions, or land surface albedo.
