What controls the historical timeseries of shortwave fluxes in the North Atlantic?

• Main Authors: Grosvenor, Daniel Peter, Carslaw, Kenneth S.
• Format: Text
• Language: English
• Published: 2022
• Subjects: North Atlantic
• Online Access: https://doi.org/10.5194/acp-2022-583; https://acp.copernicus.org/preprints/acp-2022-583/

Both aerosol radiative forcing and cloud-climate feedbacks have large effects on climate, mainly through modification of solar shortwave radiative fluxes. Here we determine what causes the long-term trends in the shortwave (SW) top-of-the-atmosphere (TOA) fluxes ( F SW ) over the North Atlantic region. The UK Earth System Model (UKESM1) and the Hadley Centre General Environment Model (HadGEM) simulate a positive F SW trend between 1850 and 1970 (increasing SW reflection) and a negative trend between 1970 and 2014. We find that the pre-1970 positive F SW trend is mainly driven by an increase in cloud droplet number concentrations due to increases in aerosol and the 1970–2014 trend is mainly driven by a decrease in cloud fraction, which we attribute mainly to cloud feedbacks caused by greenhouse gas-induced warming. Using nudged simulations where the meteorology can be controlled we show that in the pre-1970 period aerosol-induced cooling and greenhouse gas warming in coupled atmosphere-ocean simulations roughly counteract each other so that aerosol forcing is the dominant effect on F SW , with only a weak temperature-driven cloud feedback effect. However, in the post-1970 period the warming from greenhouse gases intensifies and aerosol radiative forcing falls, leading to a large overall warming and a reduction in F SW that is mainly driven by cloud feedbacks. Our results show that it is difficult to use satellite observations in the post-1970 period to evaluate and constrain the magnitude of the aerosol-cloud interaction forcing, but that cloud feedbacks might be evaluated. Comparisons to observations between 1985 and 2014 show that the simulated reduction in F SW and the increase in temperature are too strong. However, analysis shows that this temperature discrepancy can account for only part of the F SW discrepancy given the estimated model feedback strength (λ = ∂ F SW /∂ T ). This suggests a model bias in either λ or in the strength of the aerosol forcing (aerosols are reducing during this time period) is ...