Global storm-resolving models (GSRMs) are the next avenue of climate modelling. Among them is the 5-km Icosahedral Nonhydrostatic Weather and Climate Model (ICON). The high resolution allows for parameterizations of convection and clouds to be avoided. Standard-resolution models have substantial cloud biases over the Southern Ocean (SO), affecting radiation and sea surface temperature. We evaluated SO clouds in ICON and the ERA5 and MERRA-2 reanalyses. The SO is dominated by low clouds, which cannot be observed accurately from space due to overlapping clouds, attenuation, and ground clutter. Instead, we analysed about 2400 days of lidar observations from 31 voyages and a station using a ground-based lidar simulator. 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, potentially explained by their lifting condensation levels being too high. The reanalyses strongly underestimate near-surface clouds or fog. MERRA-2 tends to underestimate cloud occurrence at all heights. Less stable conditions are the most problematic for ICON and the reanalyses. In daily cloud cover, ICON and the reanalyses tend to be about 1 and 2 oktas clearer, respectively. Compared to radiosondes, potential temperature is accurate in the reanalyses, but ICON underestimates stability over the low-latitude SO and too humid in the boundary layer. MERRA-2 is too humid at all heights. SO cloud biases remain a substantial issue in the GSRM, but are an improvement over the lower-resolution reanalyses. Explicitly resolved convection and cloud processes were not enough to address the model cloud biases.
Ship-based lidar evaluation of Southern Ocean clouds in the storm-resolving general circulation model ICON and the ERA5 and MERRA-2 reanalyses
Peter Kuma1, 2, Frida A.-M. Bender1, 2, Adrian J. McDonald3, Simon P. Alexander4, 5, Greg M. McFarquhar6, 7, John J. Cassano8, 9, 10, Graeme E. Plank3, Sean Hartery11, Simon Parsons12, Sally Garrett13, Alex Schuddeboom3
1Department of Meteorology (MISU), Stockholm University, Stockholm, Sweden
2Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
3School of Physical and Chemical Sciences, University of Canterbury, Christchurch, Aotearoa/New Zealand
4Australian Antarctic Division, Kingston, Tasmania, Australia
5Australian Antarctic Program Partnership, Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Tasmania, Australia
6Cooperative Institute of Severe and High Impact Weather Research and Operations, University of Oklahoma, Norman, OK, USA
7School of Meteorology, University of Oklahoma, Norman, OK, USA
8Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA
9National Snow and Ice Data Center, University of Colorado, Boulder, CO, USA
10Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, CO, USA
11Department of Physics & Atmospheric Science, Dalhousie University, Halifax, Canada
12New South Wales Department of Planning and Environment, Sydney, New South Wales, Australia
13New Zealand Defence Force, Wellington, New Zealand
Abstract
- Archive:
- Zenodo
- DOI:
- 10.5281/zenodo.14229858
BibTeX:
@misc{kuma2024,
year={2024},
doi={10.5281/zenodo.14229858},
url={https://doi.org/10.5281/zenodo.14229858},
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},
title={Ship-based lidar evaluation of Southern Ocean clouds in the storm-resolving general circulation model ICON and the ERA5 and MERRA-2 reanalyses}
}
Document
