Articles | Volume 9, issue 5
Development and technical paper
25 May 2016
Development and technical paper |  | 25 May 2016

Evaluation of the Plant–Craig stochastic convection scheme (v2.0) in the ensemble forecasting system MOGREPS-R (24 km) based on the Unified Model (v7.3)

Richard J. Keane, Robert S. Plant, and Warren J. Tennant

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Cited articles

Abhilash, S., Sahai, A. K., Pattnaik, S., Goswami, B. N., and Kumar, A.: Extended range prediction of active-break spells of Indian summer monsoon rainfall using an ensemble prediction system in NCEP Climate Forecast System, Int. J. Climatol., 34, 98–113,, 2013.
Ball, M. A. and Plant, R. S.: Comparison of stochastic parameterization approaches in a single-column model, Phil. Trans. Roy. Soc. A, 366, 2605–2623, 2008.
Bechtold, P.: Convection in global numerical weather prediction, in: Parameterization of Atmospheric Convection. Volume 2: Current Issues and New Theories, edited by: Plant, R. S. and Yano, J.-I., chap. 15, World Scientific, Imperial College Press, 5–45, 2015.
Ben Bouallègue, Z.: Assessment and added value estimation of an ensemble approach with a focus on global radiation, Mausam, Q. J. Meteorol. Hydrol. Geophys., 66, 541–550, 2015.
Bengtsson, L., Steinheimer, M., Bechtold, P., and Geleyn, J.-F.: A stochastic parametrization for deep convection using cellular automata, Q. J. Roy. Meteor. Soc., 139, 1533–1543,, 2013.
Short summary
A widely studied stochastic deep convection scheme is evaluated over an extended forecasting period for the first time. It is found to significantly improve the probabilistic forecast for weakly forced cases – which tend to be less predictable – and to be comparable to a well-tuned reference scheme for strongly forced cases. A newly developed verification metric is applied to provide evidence that the improved probabilistic forecast is in large part due to the stochasticity of the scheme.