How does the UKESM1 climate model produce its cloud-aerosol forcing in the North Atlantic?

Climate variability in the North Atlantic influences processes such as hurricane activity and droughts. Global model simulations have identified aerosol-cloud interactions (ACIs) as an important driver of sea surface temperature variability via surface aerosol forcing. However, ACIs are a major caus...

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Bibliographic Details
Main Authors: Grosvenor, Daniel P., Carslaw, Kenneth S.
Format: Text
Language:English
Published: 2020
Subjects:
Online Access:https://doi.org/10.5194/acp-2020-502
https://www.atmos-chem-phys-discuss.net/acp-2020-502/
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Summary:Climate variability in the North Atlantic influences processes such as hurricane activity and droughts. Global model simulations have identified aerosol-cloud interactions (ACIs) as an important driver of sea surface temperature variability via surface aerosol forcing. However, ACIs are a major cause of uncertainty in climate forcing, therefore caution is needed in interpreting the results from coarse resolution, highly parameterized global models. Here we separate and quantify the components of the surface shortwave effective radiative forcing (ERF) due to aerosol in the atmosphere-only version of the UK Earth System Model (UKESM1) and evaluate the cloud properties and their radiative effects against observations. We focus on a northern region of the North Atlantic (NA) where stratocumulus clouds dominate (denoted the northern NA region) and a southern region where trade cumulus and broken stratocumlus dominate (southern NA region). Aerosol forcing was diagnosed using a pair of simulations in which the meteorology is approximately fixed via nudging to analysis; one simulation has pre-industrial (PI) and one has present-day (PD) aerosol emissions. Contributions to the surface ERF from changes in cloud fraction ( f c ), in-cloud liquid water path ( LWP ic ) and droplet number concentration ( N d ) were quantified. Over the northern NA region increases in N d and LWP ic dominate the forcing. This is likely because the high f c there precludes further large increases in f c and allows cloud brightening to act over a larger region. Over the southern NA region increases in f c dominate due to the suppression of rain by the additional aerosols. Aerosol-driven increases in macrophysical cloud properties ( LWP ic and f c ) will rely on the response of the boundary layer parameterization, along with input from the cloud microphysics scheme, which are highly uncertain processes. Model gridboxes with low-altitude clouds present in both the PI and PD dominate the forcing in both regions. In the northern NA the brightening of completely overcast low cloud scenes (100 % cloud cover, likely stratocumlus) contributes the most, whereas in the southern NA the creation of clouds with f c of around 20 % from clear skies in the PI was the largest single contributor, suggesting that trade cumulus clouds are created in response to increases in aerosol. The creation of near-overcast clouds was also important there. The correct spatial pattern, coverage and properties of clouds are important for determining the magnitude of aerosol forcing so we also assess the realism of the modelled PD clouds against satellite observations. We find that the model reproduces the spatial pattern of all the observed cloud variables well, but that there are biases. The shortwave top-of-the-atmosphere ( SW TOA ) flux is overestimated by 5.8 % in the northern NA region and 1.7 % in the southern NA, which we attribute mainly to positive biases in low-altitude f c . N d is too low by −20.6 % in the northern NA and too high by by 21.5 % in the southern NA, but does not contribute greatly to the main SW TOA biases. Cloudy-sky liquid water path mainly shows biases north of Scandinavia that reach up to between 50 and 100 % and dominate the SW TOA bias in that region. The large contribution to aerosol forcing in the UKESM1 model from highly uncertain macrophysical adjustments suggests that further targeted observations are needed to assess rain formation processes, how they depend on aerosols and the model response to precipitation in order to reduce uncertainty in climate projections.