Articles | Volume 14, issue 9
Geosci. Model Dev., 14, 5413–5434, 2021
https://doi.org/10.5194/gmd-14-5413-2021
Geosci. Model Dev., 14, 5413–5434, 2021
https://doi.org/10.5194/gmd-14-5413-2021
Development and technical paper
02 Sep 2021
Development and technical paper | 02 Sep 2021

Vertical grid refinement for stratocumulus clouds in the radiation scheme of the global climate model ECHAM6.3-HAM2.3-P3

Paolo Pelucchi et al.

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Cited articles

Bony, S. and Chepfer, H.: GCM-Oriented CALIPSO Cloud Product [dataset], available at: https://climserv.ipsl.polytechnique.fr/cfmip-obs/ (last access: 2 May 2021), 2013. a
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh, S. K., Sherwood, S., Stevens, B., and Zhang, X. Y.: Clouds and Aerosols, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2013. a
Boutle, I. A. and Morcrette, C. J.: Parametrization of area cloud fraction, Atmos. Sci. Lett., 11, 283–289, https://doi.org/10.1002/asl.293, 2010. a, b, c, d
Bretherton, C. S.: EPIC Stratocumulus Integrated Dataset, available at: https://atmos.washington.edu/~breth/EPIC/EPIC2001_Sc_ID/sc_integ_data_fr.htm (last access: December 2019), 2005. a, b, c
Bretherton, C. S. and Park, S.: A new moist turbulence parameterization in the Community Atmosphere Model, J. Climate, 22, 3422–3448, 2009. a, b
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Short summary
Stratocumulus are thin clouds whose cloud cover is underestimated in climate models partly due to overly low vertical resolution. We develop a scheme that locally refines the vertical grid based on a physical constraint for the cloud top. Global simulations show that the scheme, implemented only in the radiation routine, can increase stratocumulus cloud cover. However, this effect is poorly propagated to the simulated cloud cover. The scheme's limitations and possible ways forward are discussed.