Investigating the sign of stratocumulus adjustments to aerosols in the ICON global storm-resolving model
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Published:2024-08-06
Issue:15
Volume:24
Page:8653-8675
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ISSN:1680-7324
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Container-title:Atmospheric Chemistry and Physics
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language:en
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Short-container-title:Atmos. Chem. Phys.
Author:
Fons EmilieORCID, Naumann Ann KristinORCID, Neubauer DavidORCID, Lang Theresa, Lohmann UlrikeORCID
Abstract
Abstract. Aerosols can cause brightening of stratocumulus clouds, thereby cooling the climate. Observations and models disagree on the magnitude of this cooling, partly because of the aerosol-induced liquid water path (LWP) adjustment, with climate models predicting an increase in the LWP and satellites observing a weak decrease in response to increasing aerosols. With higher-resolution global climate models, which allow the simulation of mesoscale circulations in which stratocumulus clouds are embedded, there is hope to start bridging this gap. In this study, we present boreal summertime simulations conducted with the ICOsahedral Non-hydrostatic (ICON) global storm-resolving model (GSRM). Compared to geostationary satellite data, ICON produces realistic cloud coverage in the stratocumulus regions; however, these clouds look cumuliform, and the sign of LWP adjustments disagrees with observations. We investigate this disagreement with a causal approach, which combines time series with knowledge of cloud processes, allowing us to diagnose the sources of observation–model discrepancies. The positive ICON LWP adjustment results from a superposition of processes, with an overestimated positive response due to (1) precipitation suppression, (2) a lack of wet scavenging, and (3) cloud deepening under a weak inversion, despite (4) small negative influences from cloud-top entrainment enhancement. We also find that precipitation suppression and entrainment enhancement occur at different intensities during the day and the night, implying that daytime satellite studies suffer from selection bias. This causal methodology can guide modelers on how to modify model parameterizations and setups to reconcile conflicting studies concerning the sign and magnitude of LWP adjustments across different data sources.
Funder
Horizon 2020 Deutsche Forschungsgemeinschaft
Publisher
Copernicus GmbH
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