Abstract
Abstract. Complex aerosol–cloud–precipitation interactions lead to large differences in estimates of aerosol impacts on climate among general circulation models (GCMs) and satellite retrievals. Typically, precipitating hydrometeors are treated diagnostically in most GCMs, and their radiative effects are ignored. Here, we quantify how the treatment of precipitation influences the simulated effective radiative forcing due to aerosol–cloud interactions (ERFaci) using a state-of-the-art GCM with a two-moment prognostic precipitation scheme that incorporates the radiative effect of precipitating particles, and we investigate how microphysical process representations are related to macroscopic climate effects. Prognostic precipitation substantially weakens the magnitude of ERFaci (by approximately 54 %) compared with the traditional diagnostic scheme, and this is the result of the increased longwave (warming) and weakened shortwave (cooling) components of ERFaci. The former is attributed to additional adjustment processes induced by falling snow, and the latter stems largely from riming of snow by collection of cloud droplets. The significant reduction in ERFaci does not occur without prognostic snow, which contributes mainly by buffering the cloud response to aerosol perturbations through depleting cloud water via collection. Prognostic precipitation also alters the regional pattern of ERFaci, particularly over northern midlatitudes where snow is abundant. The treatment of precipitation is thus a highly influential controlling factor of ERFaci, contributing more than other uncertain “tunable” processes related to aerosol–cloud–precipitation interactions. This change in ERFaci caused by the treatment of precipitation is large enough to explain the existing difference in ERFaci between GCMs and observations.
Highlights
Aerosols play significant roles in the climate system (Twomey, 1977; Albrecht, 1989) by modifying the radiation budget and the hydrological cycle through interactions with clouds
Given that snow water path (SWP) is significantly larger than rainwater path (RWP) in our model (Fig. S2; see Michibata et al, 2019), and that snowflakes, with residence times longer than those of rain, are more likely to interact with clouds, the increased cloud liquid water path (CLWP) caused by anthropogenic aerosols can act as an efficient source of snow via interactions among cloud droplets and snowflakes, likely resulting in the evident robust positive relationship
Changes in RWP and SWP through PI to PD aerosol perturbations were positively correlated with those in CLWP (Fig. 3), suggesting that snow can co-exist with cloud water to a degree sufficient to buffer the cloud water response to aerosol perturbations (Fig. 4)
Summary
Aerosols play significant roles in the climate system (Twomey, 1977; Albrecht, 1989) by modifying the radiation budget (aerosol–radiation interactions, ARIs) and the hydrological cycle through interactions with clouds (aerosol– cloud interactions, ACIs). Aerosol-induced radiative forcing at the top of the atmosphere (TOA) that includes rapid adjustments caused by ACI, termed effective radiative forcing (ERFaci), varies widely among GCMs (Shindell et al, 2013; Zelinka et al, 2014) This results in a “best estimate” of global annual mean ERFaci of −0.45 W m−2 with a 90 % confidence interval of −1.2 to 0.0 W m−2 (Boucher et al, 2013), as reported in the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC AR5). This single-model approach has the advantage of not being affected by varying physics representations, as in the case of multi-model analysis (see “Materials and methods”)
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