Preprints
https://doi.org/10.5194/egusphere-2026-5350
https://doi.org/10.5194/egusphere-2026-5350
06 Oct 2026
 | 06 Oct 2026
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Drizzle drives model differences in the Southeastern Atlantic Stratocumulus Transitions with Aerosol-Rain-Radiation interactions (SEA STARR) large eddy simulation intercomparison project

Michael S. Diamond, Andrew S. Ackerman, Alejandro Baró Pérez, Ann M. Fridlind, Ehsan Erfani, Caspar Jungbacker, Hyunho Lee, David Painemal, Frida A.-M. Bender, Annica M. L. Ekman, Franziska Glassmeier, Graham Feingold, Fredrik Jansson, David A. Johnson, Matthias Schwarz, Robert Wood, Takanobu Yamaguchi, Jianhao Zhang, Xiaoli Zhou, and Paquita Zuidema

Abstract. The transition from overcast stratocumulus clouds to broken cumulus cloud fields as air is advected over warmer waters is important for controlling cloud cover and thus the radiative budget in the subtropics. Stratocumulus clouds can transition into scattered cumulus via an entrainment-driven “deepening-warming” process or into an open mesoscale cellular convective organization via a precipitation-driven “drizzle-depletion” process. The Southeastern Atlantic Stratocumulus Transitions with Aerosol-Rain-Radiation interactions (SEA STARR) large eddy simulation (LES) intercomparison project described herein uses a composite trajectory of cloud transitions in the southeastern Atlantic to assess the extent to which different LES model setups simulate similar deepening-warming or drizzle-depletion transitions under identical meteorological and aerosol forcings. Results are evaluated in light of observations from the ORACLES, CLARIFY, and LASIC field campaigns.

The default setup includes abundant smoke (~1,000 mg-1) from southern African biomass burning and is compared with simulations using the same large-scale meteorology but cleaner (100 or 30 mg-1) free tropospheric aerosol concentrations. In the control, all five LES models simulate deepening-warming transitions that track satellite observations in terms of cloud fraction; exhibit boundary layer deepening somewhat greater than is consistent with observations; and maintain higher cloud droplet number concentrations than observed during nearby aircraft campaigns despite similar below-cloud aerosol number concentrations. In the cleaner cases, however, some models produce drizzle-depletion transitions while others maintain deepening-warming transitions. LES model differences are tied to large discrepancies in simulated rain formation for a given cloud state in terms of total condensate and droplet concentration.

Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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Michael S. Diamond, Andrew S. Ackerman, Alejandro Baró Pérez, Ann M. Fridlind, Ehsan Erfani, Caspar Jungbacker, Hyunho Lee, David Painemal, Frida A.-M. Bender, Annica M. L. Ekman, Franziska Glassmeier, Graham Feingold, Fredrik Jansson, David A. Johnson, Matthias Schwarz, Robert Wood, Takanobu Yamaguchi, Jianhao Zhang, Xiaoli Zhou, and Paquita Zuidema

Status: open (until 17 Nov 2026)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Michael S. Diamond, Andrew S. Ackerman, Alejandro Baró Pérez, Ann M. Fridlind, Ehsan Erfani, Caspar Jungbacker, Hyunho Lee, David Painemal, Frida A.-M. Bender, Annica M. L. Ekman, Franziska Glassmeier, Graham Feingold, Fredrik Jansson, David A. Johnson, Matthias Schwarz, Robert Wood, Takanobu Yamaguchi, Jianhao Zhang, Xiaoli Zhou, and Paquita Zuidema

Data sets

LES/SCM driver files for the SEA STARR (SE Atlantic Stratocumulus Transitions with Aerosol-Rain-Radiation interactions) intercomparison project Michael S. Diamond https://doi.org/10.5281/zenodo.22241697

SEA STARR output contribution from NOAA-SAM Michael S. Diamond https://doi.org/10.5281/zenodo.22237166

SEA STARR output contribution from UW-SAM Michael S. Diamond and Ehsan Erfani https://doi.org/10.5281/zenodo.22238625

SEA STARR output contribution from MIMICA Michael S. Diamond and Alejandro Baró Pérez https://doi.org/10.5281/zenodo.22237423

SEA STARR output contribution from DHARMA Michael S. Diamond et al. https://doi.org/10.5281/zenodo.22238263

SEA STARR output contribution from DALES Michael S. Diamond and Caspar Jungbacker https://doi.org/10.5281/zenodo.22238009

Suite of Aerosol, Cloud, and Related Data Acquired Aboard P3 During ORACLES 2016, Version 2 ORACLES Science Team https://doi.org/10.5067/Suborbital/ORACLES/P3/2016_V2

Suite of Aerosol, Cloud, and Related Data Acquired Aboard P3 During ORACLES 2017, Version 2 ORACLES Science Team https://doi.org/10.5067/Suborbital/ORACLES/P3/2017_V2

Suite of Aerosol, Cloud, and Related Data Acquired Aboard P3 During ORACLES 2018, Version 2 ORACLES Science Team https://doi.org/10.5067/Suborbital/ORACLES/P3/2018_V2

CLARIFY: in-situ airborne observations by the FAAM BAE-146 aircraft Facility for Airborne Atmospheric Measurements, Natural Environment Research Council, and Met Office http://catalogue.ceda.ac.uk/uuid/38ab7089781a4560b067dd6c20af3769

Ultra-High Sensitivity Aerosol Spectrometer (AOSUHSAS). 2017-08-01 to 2017-08-31 ARM user facility https://doi.org/10.5439/1333828

Balloon-Borne Sounding System (SONDEWNPN). 2016-04-29 to 2017-11-01, ARM Mobile Facility (ASI) Airport Site, Ascension Island, South Atlantic Ocean; Supplemental Site (S1) ARM user facility https://doi.org/10.5439/1021460

CLDPROP_M3_MODIS_Aqua - MODIS/Aqua Cloud Properties Level 3 monthly, 1x1 degree grid NASA LAADS DAAC https://doi.org/10.5067/MODIS/CLDPROP_M3_MODIS_Aqua.011

Model code and software

System for Atmospheric Modeling Marat F. Khairoutdinov http://rossby.msrc.sunysb.edu/SAM.html

MIMICAV5 Matthias Brakebusch https://bitbucket.org/matthiasbrakebusch/mimicav5/src/master/

dalesteam/dales: DALES 4.4.2 (v4.4.2) Sylwester Arabas et al. https://doi.org/10.5281/zenodo.11479354

Interactive computing environment

michael-s-diamond/SEA_STARR: Version 20260902 Michael S. Diamond https://doi.org/10.5281/zenodo.22266292

Michael S. Diamond, Andrew S. Ackerman, Alejandro Baró Pérez, Ann M. Fridlind, Ehsan Erfani, Caspar Jungbacker, Hyunho Lee, David Painemal, Frida A.-M. Bender, Annica M. L. Ekman, Franziska Glassmeier, Graham Feingold, Fredrik Jansson, David A. Johnson, Matthias Schwarz, Robert Wood, Takanobu Yamaguchi, Jianhao Zhang, Xiaoli Zhou, and Paquita Zuidema
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Latest update: 06 Oct 2026
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Short summary
We compare how cloud resolving models represent an important cloud transition over the subtropical oceans. Clouds can either break up by deepening and drying out or by raining and forming an open cell pattern. Compared to observations, the clouds deepen a bit too much and get too polluted when smoke is present. In clean conditions, some models drizzle and break up into open cells while others barely rain; the model spread stems from different rain amounts for similar clouds.
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