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Understanding aerosol–cloud interactions using a single-column model for a cold-air outbreak case during the ACTIVATE campaign

Authors :
S. Tang
H. Wang
X.-Y. Li
J. Chen
A. Sorooshian
X. Zeng
E. Crosbie
K. L. Thornhill
L. D. Ziemba
C. Voigt
Source :
Atmospheric Chemistry and Physics, Vol 24, Pp 10073-10092 (2024)
Publication Year :
2024
Publisher :
Copernicus Publications, 2024.

Abstract

Marine boundary layer clouds play a critical role in Earth's energy balance. Their microphysical and radiative properties are highly impacted by ambient aerosols and dynamic forcings. In this study, we evaluate the representation of these clouds and related aerosol–cloud interaction processes in the single-column version of the E3SM climate model (SCM) against field measurements collected during the NASA ACTIVATE campaign over the western North Atlantic, as well as intercompare results with high-resolution process level models. We show that E3SM SCM reproduces the macrophysical properties of post-frontal boundary layer clouds in a cold-air outbreak (CAO) case well. However, it generates fewer but larger cloud droplets compared to aircraft measurements. Further sensitivity tests show that the underestimation of both aerosol number concentration and vertical velocity variance contributes to this bias. Aerosol–cloud interactions are examined by perturbing prescribed aerosol properties in E3SM SCM with fixed dynamics. Higher aerosol number concentration or hygroscopicity leads to more numerous but smaller cloud droplets, resulting in a stronger cooling via shortwave cloud forcing. This apparent Twomey effect is consistent with prior climate model studies. The cloud liquid water path shows a weakly positive relation with cloud droplet number concentration due to precipitation suppression. This weak aerosol effect on cloud macrophysics may be attributed to the dominant impact of strong dynamical forcing associated with the CAO. Our findings indicate that the SCM framework is a key tool to bridge the gap between climate models, process level models, and field observations to facilitate process level understanding.

Subjects

Subjects :
Physics
QC1-999
Chemistry
QD1-999

Details

Language :
English
ISSN :
16807316 and 16807324
Volume :
24
Database :
Directory of Open Access Journals
Journal :
Atmospheric Chemistry and Physics
Publication Type :
Academic Journal
Accession number :
edsdoj.52c5ad74585544bfb5e452341e941d2a
Document Type :
article
Full Text :
https://doi.org/10.5194/acp-24-10073-2024