Global storm resolving models (GSRMs) represent the next generation of global climate models. One of them is a 5-km Icosahedral Nonhydrostatic Weather and Climate Model (ICON). Its high resolution means that parameterizations of convection and clouds, including subgrid-scale clouds, are omitted, relying on explicit simulation but necessarily utilizing microphysics and turbulence parameterizations. Standard-resolution (10–100 km) models, which use convection and cloud parameterizations, have substantial cloud biases over the Southern Ocean (SO), adversely affecting radiation and sea surface temperature. The SO is dominated by low clouds, which cannot be observed accurately from space due to overlapping clouds, attenuation, and ground clutter. We evaluated SO clouds in ICON and the ERA5 and MERRA-2 reanalyses using approximately 2400 days of lidar observations and 2300 radiosonde profiles from 31 voyages and a Macquarie Island station during 2010–2021, compared to the models using a ground-based lidar simulator. We found that ICON and the reanalyses underestimate the total cloud fraction by about 10 and 20%, respectively. ICON and ERA5 overestimate the cloud occurrence peak at about 500 m, associated with underestimated lower tropospheric stability and overestimated lifting condensation level. The reanalyses strongly underestimate fog and very low-level clouds, and MERRA-2 underestimates cloud occurrence at almost all heights. Outgoing shortwave radiation is overestimated in MERRA-2, implying a “too few, too bright” cloud problem. SO cloud and fog biases are a substantial issue in the analyzed models and result in shortwave and longwave radiation biases.
Ship-based lidar evaluation of Southern Ocean low clouds in the storm-resolving general circulation model ICON and the ERA5 and MERRA-2 reanalyses
Peter Kuma1, 2, 3, 4,
Frida A.-M. Bender1, 2,
Adrian J. McDonald3,
Simon P. Alexander5, 6,
Greg M. McFarquhar7, 8,
John J. Cassano9, 10, 11,
Graeme E. Plank3,
Sean Hartery3, 12,
Simon Parsons3, 13,
Sally Garrett14,
…
Alex Schuddeboom3,
Anna Possner4
1Department of Meteorology (MISU), Stockholm University, Stockholm, Sweden
11Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, CO, USA
2Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
3School of Physical and Chemical Sciences, University of Canterbury, Christchurch, Aotearoa/New Zealand
4Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, Frankfurt am Main, Hesse, Germany
5Australian Antarctic Division, Kingston, Tasmania, Australia
6Australian Antarctic Program Partnership, Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Tasmania, Australia
7Cooperative Institute of Severe and High Impact Weather Research and Operations, University of Oklahoma, Norman, OK, USA
8School of Meteorology, University of Oklahoma, Norman, OK, USA
9Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA
10National Snow and Ice Data Center, University of Colorado, Boulder, CO, USA
…
12Department of Physics & Atmospheric Science, Dalhousie University, Halifax, Canada
13New South Wales Department of Planning and Environment, Sydney, New South Wales, Australia
14New Zealand Defence Force, Wellington, New Zealand
Abstract
- Note:
- in review in Journal of Geophysical Research: Atmospheres
- Archive:
- Zenodo
- DOI:
- 10.5281/zenodo.14070222
- Submitted:
- 21 July 2025
- License:
- Open access / Creative Commons Attribution 4.0 (CC BY 4.0)
BibTeX:
@article{kuma2025,
year={2025},
note={in review in Journal of Geophysical Research: Atmospheres},
doi={10.5281/zenodo.14070222},
url={https://doi.org/10.5281/zenodo.14070222},
author={Kuma, Peter and Bender, Frida A.-M. and McDonald, Adrian J. and Alexander, Simon P. and McFarquhar, Greg M. and Cassano, John J. and Plank, Graeme E. and Hartery, Sean and Parsons, Simon and Garrett, Sally and Schuddeboom, Alex and Possner, Anna},
title={Ship-based lidar evaluation of Southern Ocean low clouds in the storm-resolving general circulation model ICON and the ERA5 and MERRA-2 reanalyses}
}
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