Articles | Volume 17, issue 21
https://doi.org/10.5194/gmd-17-8069-2024
https://doi.org/10.5194/gmd-17-8069-2024
Model evaluation paper
 | 
12 Nov 2024
Model evaluation paper |  | 12 Nov 2024

The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators

Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding

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Cited articles

Abel, S. J. and Boutle, I. A.: An Improved Representation of the Raindrop Size Distribution for Single-Moment Microphysics Schemes, Q. J. Roy. Meteorol. Soc., 138, 2151–2162, 2012. a
Ahlgrimm, M. and Forbes, R.: Improving the Representation of Low Clouds and Drizzle in the ECMWF Model Based on ARM Observations from the Azores, Mon. Weather Rev., 142, 668–685, 2014. a
ARM: The world's premier ground-based observations facility advancing atmospheric and climate research, https://www.arm.gov/ (last access: 5 November 2024), 2024. a
Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., van den Hurk, B., Hirschi, M., and Betts, A. K.: A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System, J. Hydrometeorol., 10, 623–643, 2009. a
Bechtold, P., Kohler, M., Jung, T., Doblas-Reyes, F., Leutbecher, M., Rodwell, M. J., Vitart, F., and Balsamo, G.: Advances in Simulating Atmospheric Variability with the ECMWF Model: From Synoptic to Decadal Time-Scales, Q. J. Roy. Meteorol. Soc., 134, 1337–1351, 2008. a
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
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