posted on 2024-03-21, 12:41authored byE Gryspeerdt, AC Povey, RG Grainger, O Hasekamp, N Christina Hsu, JP Mulcahy, AM Sayer, A Sorooshian
Atmospheric aerosols and their impact on cloud properties remain the largest uncertainty in the human forcing of the climate system. By increasing the concentration of cloud droplets (Nd), aerosols reduce droplet size and increase the reflectivity of clouds (a negative radiative forcing). Central to this climate impact is the susceptibility of cloud droplet number to aerosol (β), the diversity of which explains much of the variation in the radiative forcing from aerosol-cloud interactions (RFaci) in global climate models. This has made measuring β a key target for developing observational constraints of the aerosol forcing. While the aerosol burden of the clean, pre-industrial atmosphere has been demonstrated as a key uncertainty for the aerosol forcing, here we show that the behaviour of clouds under these clean conditions is of equal importance for understanding the spread in radiative forcing estimates between models and observations. This means that the uncertainty in the aerosol impact on clouds is, counterintuitively, driven by situations with little aerosol. Discarding clean conditions produces a close agreement between different model and observational estimates of the cloud response to aerosol but does not provide a strong constraint on the RFaci. This makes constraining aerosol behaviour in clean conditions an important goal for future observational studies.
Funding
Royal Society University Research Fellowship (URF/R1/191602)
Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE)
Gryspeerdt, E., Povey, A. C., Grainger, R. G., Hasekamp, O., Hsu, N. C., Mulcahy, J. P., Sayer, A. M., and Sorooshian, A.: Uncertainty in aerosol–cloud radiative forcing is driven by clean conditions, Atmos. Chem. Phys., 23, 4115–4122, https://doi.org/10.5194/acp-23-4115-2023, 2023.
Author affiliation
College of Science & Engineering/Physics & Astronomy
The MODIS data were obtained through the Level 1 and Atmosphere Archive and Distribution System (LAADS). The gridded Nd data were obtained through the Centre for Environmental Data Analysis (CEDA). The model data were obtained through the AeroCom initiative (http://aerocom.met.no, last access: 11 March 2023). MERRA-2 data were obtained from the Goddard Earth Sciences Data and Information Services Center (GES DISC).