Uncertainty in aerosol-cloud radiative forcing is driven by clean conditions
(2022)
Is anthropogenic global warming accelerating?
Journal of Climate American Meteorological Society 35:24 (2022) 4273-4290
Abstract:
Estimates of the anthropogenic effective radiative forcing (ERF) trend have increased by 50% since 2000 (+0.4W/m2/decade in 2000-2009 to +0.6W/m2/decade in 2010-2019), the majority of which is driven by changes in the aerosol ERF trend, due to aerosol emissions reductions. Here we study the extent to which observations of the climate system agree with these ERF assumptions. We use a large ERF ensemble from IPCC’s Sixth Assessment Report (AR6) to attribute the anthropogenic contributions to global mean surface temperature (GMST), top-of-atmosphere radiative flux, and aerosol optical depth observations. The GMST trend has increased from +0.18°C/decade in 2000-2009 to +0.35°C/decade in 2010-2019, coinciding with the anthropogenic warming trend rising from +0.19°C/decade in 2000-2009 to +0.24°C/decade in 2010-2019. This, and observed trends in top-of-atmosphere radiative fluxes and aerosol optical depths support the claim of an aerosol-induced temporary acceleration in the rate of warming. However, all three observation datasets additionally suggest smaller aerosol ERF trend changes are compatible with observations since 2000, since radiative flux and GMST trends are significantly influenced by internal variability over this period. A zero-trend-change aerosol ERF scenario results in a much smaller anthropogenic warming acceleration since 2000, but is poorly represented in AR6’s ERF ensemble. Short-term ERF trends are difficult to verify using observations, so caution is required in predictions or policy judgments that depend on them, such as estimates of current anthropogenic warming trend, and the time remaining to, or the outstanding carbon budget consistent with, 1.5°C warming. Further systematic research focused on quantifying trends and early identification of acceleration or deceleration is required.Opportunistic experiments to constrain aerosol effective radiative forcing
Atmospheric Chemistry and Physics Copernicus Publications 22:1 (2022) 641-674
Abstract:
Aerosol–cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide “opportunistic experiments” (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.Supplementary material to "Opportunistic Experiments to Constrain Aerosol Effective Radiative Forcing"
(2021)
Cloud_cci ATSR-2 and AATSR data set version 3: a 17-year climatology of global cloud and radiation properties
Earth System Science Data Copernicus Publications 12:3 (2020) 2121-2135