The Cold-Air Outbreaks in the Marine Boundary Layer Experiment model-observation intercomparison project (COMBLE-MIP) – Part 1: Model specification, observational constraints, and preliminary findings
Journal article, 2026
Models struggle to represent the coupled microphysical, turbulent and radiative processes within widespread, long-lived marine cold-air outbreak (CAO) cloud fields, contributing to forecast and climate biases. Here we combine ground-based and satellite measurements to initialize and constrain large-eddy simulations (LES) of cloud field evolution with distance downwind from the marginal ice zone during a strong, highly supercooled and convective CAO observed during the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE). LES results are compared with large-scale models run in single-column model (SCM) mode, providing an observation-constrained framework for large-scale model evaluation and future improvements. All models reproduce rapid cloud formation off the ice edge, and a monotonic ascent of downwind cloud-top heights, closely linked with time-integrated surface heat fluxes. LES generally reproduce domain-mean observational targets using a modest test domain (25×25 km2), and a larger domain (125×125 km2) enables better reproducing the observed growth of convective cell sizes. In realistic mixed-phase LES compared with liquid-only simulations, ice processes lead to thinner, broken cloud decks and substantially reduced cloud radiative effects on top-of-atmosphere longwave fluxes. By contrast, mixed-phase SCM simulations generally underpredict the radiative impact of ice, primarily owing to insufficient reduction of cloud cover. Results indicate that cellular cloud structure is qualitatively captured by LES, and thus LES could provide guidance to improvement of large-scale model physics schemes. Follow-on work will extend these results to larger domains, apply objective analysis of mesoscale structure, and include prognostic aerosol properties for droplet and heterogeneous ice formation.
Author
Timothy W. Juliano
National Science Foundation
Florian Tornow
National Aeronautics and Space Administration (NASA)
Columbia University
Ann M. Fridlind
National Aeronautics and Space Administration (NASA)
Andrew S. Ackerman
National Aeronautics and Space Administration (NASA)
Gregory S. Elsaesser
National Aeronautics and Space Administration (NASA)
Columbia University
Bart Geerts
University of Wyoming
Christian P. Lackner
University of Wyoming
David Painemal
National Aeronautics and Space Administration (NASA)
Israel Silber
Pacific Northwest National Laboratory
Mikhail Ovchinnikov
Pacific Northwest National Laboratory
G. Svensson
Stockholm University
Michael Tjernström
Stockholm University
Peng Wu
Pacific Northwest National Laboratory
Alejandro Baró Pérez
Stockholm University
Chalmers, Space, Earth and Environment, Geoscience and Remote Sensing
Peter Bogenschutz
Lawrence Livermore National Laboratory
Dmitry Chechin
Russian Academy of Sciences
Kamal Kant Chandrakar
National Science Foundation
Jan Chylik
University of Cologne
Andrey Debolskiy
Moscow State University
Rostislav Fadeev
Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences
Anu Gupta
University of Hyogo
Luisa Ickes
Chalmers, Space, Earth and Environment, Geoscience and Remote Sensing
Michail Karalis
Stockholm University
Martin Köhler
Deutscher Wetterdienst
Branko Kosović
Johns Hopkins University
Peter Kuma
Stockholm University
Goethe University Frankfurt
Weiwei Li
National Science Foundation
Evgeny Mortikov
Moscow State University
Hugh Morrison
National Science Foundation
Roel A.J. Neggers
University of Cologne
Anna Possner
Goethe University Frankfurt
Tomi Raatikainen
Finnish Meteorological Institute (FMI)
Lea Raillard
Pierre and Marie Curie University (UPMC)
Swiss Federal Institute of Technology in Lausanne (EPFL)
Sami Romakkaniemi
Finnish Meteorological Institute (FMI)
Niklas Schnierstein
University of Cologne
Shin ichiro Shima
University of Hyogo
Nikita Silin
Moscow State University
Mikhail Tolstykh
Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences
Étienne Vignon
Pierre and Marie Curie University (UPMC)
Lulin Xue
National Science Foundation
Meng Zhang
Lawrence Livermore National Laboratory
Xue Zheng
Lawrence Livermore National Laboratory
Atmospheric Chemistry and Physics
1680-7316 (ISSN) 1680-7324 (eISSN)
Vol. 26 18 13267-13302Subject Categories (SSIF 2025)
Meteorology and Atmospheric Sciences
DOI
10.5194/acp-26-13267-2026