Large-eddy simulations of marine boundary-layer clouds associated with cold air outbreaks during the ACTIVATE campaign-part 1: Case setup and sensitivities to large-scale forcings
Xiang-Yu Li, Hailong Wang, Jingyi Chen, Satoshi Endo, Geet George,, Brian Cairns, Seethala Chellappan, Xubin Zeng, Simon Kirschler, Christiane, Voigt, Armin Sorooshian, Ewan Crosbie, Gao Chen, Richard Anthony Ferrare,, William I. Gustafson, Johnathan W Hair, Mary M Kleb

TL;DR
This study uses large-eddy simulations driven by reanalysis data to investigate boundary-layer cloud processes during cold air outbreaks, emphasizing the importance of large-scale forcings and surface heat fluxes for accurate modeling.
Contribution
It demonstrates how reanalysis-derived large-scale forcings improve LES accuracy in simulating boundary-layer clouds during cold air outbreaks.
Findings
Large-scale thermodynamic advection influences boundary-layer evolution.
Surface heat fluxes significantly affect liquid water path.
LES results agree well with ACTIVATE measurements.
Abstract
Large-eddy simulation (LES) is able to capture key boundary-layer (BL) turbulence and cloud processes. Yet, large-scale forcing and surface turbulent fluxes of sensible and latent heat are often poorly prescribed for LES simulations. We derive these quantities from measurements and reanalysis obtained for two cold air outbreak (CAO) events during Phase I of the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) in February-March 2020. We study the two contrasting CAO cases by performing LES and test the sensitivity of BL structure and clouds to large-scale forcings and turbulent heat fluxes. Profiles of atmospheric state and large-scale divergence and surface turbulent heat fluxes obtained from the reanalysis data ERA5 agree reasonably well with those derived from ACTIVATE field measurements for both cases at the sampling time and location. Therefore,…
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Taxonomy
TopicsAtmospheric aerosols and clouds · Meteorological Phenomena and Simulations · Climate variability and models
