Articles | Volume 16, issue 7
https://doi.org/10.5194/gmd-16-1909-2023
https://doi.org/10.5194/gmd-16-1909-2023
Development and technical paper
 | 
06 Apr 2023
Development and technical paper |  | 06 Apr 2023

Improving the representation of shallow cumulus convection with the simplified-higher-order-closure–mass-flux (SHOC+MF v1.0) approach

Maria J. Chinita, Mikael Witte, Marcin J. Kurowski, Joao Teixeira, Kay Suselj, Georgios Matheou, and Peter Bogenschutz

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Cited articles

Beljaars, A., Balsamo, G., Bechtold, P., Bozzo, A., Forbes, R., Hogan, R. J., Köhler, M., Morcrette, J. J., Tompkins, A. M., Viterbo, P., and Wedi, N.: The Numerics of Physical Parametrization in the ECMWF Model, Front. Earth Sci., 6, 1–18, https://doi.org/10.3389/feart.2018.00137, 2018. 
Betts, A. K.: Non-precipitating cumulus convection and its parameterization, Q. J. Roy. Meteor. Soc., 99, 178–196, https://doi.org/10.1002/qj.49709941915, 1973. 
Blackadar, A. K.: The vertical distribution of wind and turbulent exchange in a neutral atmosphere, J. Geophys. Res., 67, 3095–3102, 1962. 
Bogenschutz, P. A. and Krueger, S. K.: A simplified PDF parameterization of subgrid-scale clouds and turbulence for cloud-resolving models, J. Adv. Model. Earth Sy., 5, 195–211, https://doi.org/10.1002/jame.20018, 2013. 
Bogenschutz, P. A., Tang, S., Caldwell, P. M., Xie, S., Lin, W., and Chen, Y.-S.: The E3SM version 1 single-column model, Geosci. Model Dev., 13, 4443–4458, https://doi.org/10.5194/gmd-13-4443-2020, 2020. 
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Short summary
Low clouds are one of the largest sources of uncertainty in climate prediction. In this paper, we introduce the first version of the unified turbulence and shallow convection parameterization named SHOC+MF developed to improve the representation of shallow cumulus clouds in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM). Here, we also show promising preliminary results in a single-column model framework for two benchmark cases of shallow cumulus convection.
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