Bounding Global Aerosol Radiative Forcing of Climate Change

Abstract

Aerosols interact with radiation and clouds. Substantial progress made over the past 40 years in observing, understanding, and modeling these processes helped quantify the imbalance in the Earth's radiation budget caused by anthropogenic aerosols, called aerosol radiative forcing, but uncertainties remain large. This review provides a new range of aerosol radiative forcing over the industrial era based on multiple, traceable, and arguable lines of evidence, including modeling approaches, theoretical considerations, and observations. Improved understanding of aerosol absorption and the causes of trends in surface radiative fluxes constrain the forcing from aerosol‐radiation interactions. A robust theoretical foundation and convincing evidence constrain the forcing caused by aerosol‐driven increases in liquid cloud droplet number concentration. However, the influence of anthropogenic aerosols on cloud liquid water content and cloud fraction is less clear, and the influence on mixed‐phase and ice clouds remains poorly constrained. Observed changes in surface temperature and radiative fluxes provide additional constraints. These multiple lines of evidence lead to a 68% confidence interval for the total aerosol effective radiative forcing of ‐1.6 to ‐0.6 W m−2, or ‐2.0 to ‐0.4 W m−2 with a 90% likelihood. Those intervals are of similar width to the last Intergovernmental Panel on Climate Change assessment but shifted toward more negative values. The uncertainty will narrow in the future by continuing to critically combine multiple lines of evidence, especially those addressing industrial‐era changes in aerosol sources and aerosol effects on liquid cloud amount and on ice clouds.

Synergetic Satellite Trend Analysis of Aerosol and Warm Cloud Properties ver Ocean and Its Implication for Aerosol‐Cloud Interactions

“…Our results indicate that over regions with significant long-term trends of aerosol loading and CDNC (e.g., EUS and WEU regions), ACI based on the long-term trend are significant. For example, dlnCDNC/dlnAOD is 0.39 over EUS and 0.63 over WEU, which are closer to those derived from ground and aircraft observations (e.g., Bellouin et al, 2019;McComiskey et al, 2009). This provides a more reliable way for estimating ACI and for further confronting model simulations over these regions.…”

“…ACI are quantified here as dlnCDNC/dlnAOD or dlnCDnC/dlnAI, which indicates the sensitivity of CDNC to aerosol perturbation. ACI have been widely documented using ground-based observations, in situ aircraft observations, and satellite observations (e.g., Bellouin et al, 2019;Feingold et al, 2003;McComiskey et al, 2009). However, most of previous studies are based on instantaneous observations of aerosol and cloud properties, which are often difficult to isolate microphysical effects from other non-microphysical factors.…”

“…Journal of Geophysical Research: Atmospheres ground and aircraft observations (e.g., Bellouin et al, 2019;McComiskey et al, 2009). This provides a more reliable way for quantifying ACI.…”

Substantial Cloud Brightening From Shipping in Subtropical Low Clouds

“…From equation (26), we estimate global average (diurnally averaged) values of Δln(N d ) of 0.29 (0.18 to 0.43) for stratiform clouds and 0.13 (0.04 to 0.23) for cumuliform clouds. These values are fairly large considering the global average bulk estimate of 0.06 to 0.18 assessed in Bellouin et al (2019).…”

Sensitivity of Radiative Fluxes to Aerosols in the ALADIN-HIRLAM Numerical Weather Prediction System

“…Recent studies, such as those by [14,15], provide additional motivation to improve how aerosols are taken into account in short-range regional numerical weather prediction (NWP) models and not just in global medium-range forecasting and climate models [16][17][18]. The direct radiative effect of aerosols on weather and climate is much better quantified than indirect effects [19,20] because of the greater physical understanding of the aerosol radiative effects compared to the impact of aerosols on clouds and precipitation. This suggests that focusing on improving aerosol radiative transfer parametrizations is worthwhile in limited-area NWP models.Regional integrated weather-chemistry models [21] are computationally demanding, thus mainly used for research.…”