Opinion: The importance of historical and paleoclimate aerosol radiative effects

Abstract

Abstract. Estimating past aerosol radiative effects and their uncertainties is an important topic in climate science. Aerosol radiative effects propagate into large uncertainties in estimates of how present and future climate evolves with changing greenhouse gas emissions. A deeper understanding of how aerosols affected the atmospheric energy budget under past climates is hindered in part by a lack of relevant paleo-observations and in part because less attention has been paid to the problem. Because of the lack of information we do not seek here to determine the change in the radiative forcing due to aerosol changes but rather to estimate the uncertainties in those changes. Here we argue that current uncertainties from emission uncertainties (90 % confidence interval range spanning 2.8 W m−2) are just as large as model spread uncertainties (2.8 W m−2) in calculating preindustrial to present-day aerosol radiative effects. There are no estimates of radiative forcing for important aerosols such as wildfire and dust aerosols in most paleoclimate time periods. However, qualitative analysis of paleoclimate proxies suggests that changes in aerosols between different past climates are similar in magnitude to changes in aerosols between the preindustrial and present day; plus, there is the added uncertainty from the variability in aerosols and fires in the preindustrial. From the limited literature we crudely estimate a paleoclimate aerosol uncertainty for the Last Glacial Maximum relative to preindustrial of 4.8 W m−2, and we estimate the uncertainty in the aerosol feedback in the natural Earth system over the paleoclimate (Last Glacial Maximum to preindustrial) to be about 3.2 W m−2 K−1. In order to more accurately assess the uncertainty in historical aerosol radiative effects, we propose a new model intercomparison project, which would include multiple plausible emission scenarios tested across a range of state-of-the-art climate models over the historical period. These emission scenarios would then be compared to the available independent aerosol observations to constrain which are most probable. In addition, future efforts should work to characterize and constrain paleo-aerosol forcings and uncertainties. Careful propagation of aerosol uncertainties in the literature is required to ensure an accurate quantification of uncertainties in projections of future climate changes.

A global dust emission dataset for estimating dust radiative forcings in climate models

“…The major problem of the ESMs' missing long-term dust trend is that ESMs will not capture the 85 radiative forcing (RF) due to the increased dust and its interactions with radiation, clouds, atmospheric chemistry, snow and ice, and biogeochemistry (Kok et al, 2023). Furthermore, since current estimates of the climate sensitivity (K or K W -1 m 2 ) to greenhouse gas (GHG) warming depend on the historical aerosol RF, missing the dust RF likely causes ESMs to underestimate the overall negative aerosol RF, which could in turn affect models' climate sensitivity (e.g., Andreae et al, 2005;Mahowald et al, 2024). Hence, the 90 inadequate representation of the historical dust increase in ESMs may affect RFs, climate sensitivity, and ultimately mislead climate change predictions, such as those reported by the Intergovernmental Panel on Climate Change (IPCC, 2021).…”

Comment on egusphere-2024-1124

“…The major problem of the ESMs' missing long-term dust trend is that ESMs will not capture the 85 radiative forcing (RF) due to the increased dust and its interactions with radiation, clouds, atmospheric chemistry, snow and ice, and biogeochemistry (Kok et al, 2023). Furthermore, since current estimates of the climate sensitivity (K or K W -1 m 2 ) to greenhouse gas (GHG) warming depend on the historical aerosol RF, missing the dust RF likely causes ESMs to underestimate the overall negative aerosol RF, which could in turn affect models' climate sensitivity (e.g., Andreae et al, 2005;Mahowald et al, 2024). Hence, the 90 inadequate representation of the historical dust increase in ESMs may affect RFs, climate sensitivity, and ultimately mislead climate change predictions, such as those reported by the Intergovernmental Panel on Climate Change (IPCC, 2021).…”