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Impact of a stochastic parametrization of cumulus convection, using cellular automata, in a mesoscale ensemble prediction system
SMHI, Research Department, Meteorology.ORCID iD: 0000-0001-8756-0331
SMHI, Research Department, Meteorology.ORCID iD: 0000-0003-0524-6440
2016 (English)In: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 142, no 695, 1150-1159 p.Article in journal (Refereed) Published
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Abstract [en]

A stochastic parametrization for deep convection, based on cellular automata, has been evaluated in the high-resolution (2.5 km) ensemble prediction system Hirlam Aladin Regional Mesoscale Operational NWP Ensemble Prediction System (HarmonEPS). We studied whether such a stochastic physical parametrization, whilst implemented in a deterministic forecast model, can have an impact on the performance of the uncertainty estimates given by an ensemble prediction system. Various feedback mechanisms in the parametrization were studied with respect to ensemble spread and skill, in both subgrid and resolved precipitation fields. It was found that the stochastic parametrization improves the model skill in general, by reducing a positive bias in precipitation. This reduction in bias, however, led to a reduction in ensemble spread of precipitation. Overall, scores that measure the accuracy and reliability of probabilistic predictions indicate that the net impact (improved skill, degraded spread) of the ensemble prediction system is improved for 6 h accumulated precipitation with the stochastic parametrization and is rather neutral for other quantities examined.

Place, publisher, year, edition, pages
2016. Vol. 142, no 695, 1150-1159 p.
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
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URN: urn:nbn:se:smhi:diva-2029DOI: 10.1002/qj.2720ISI: 000372951300051OAI: oai:DiVA.org:smhi-2029DiVA: diva2:925734
Available from: 2016-05-03 Created: 2016-05-02 Last updated: 2016-05-04Bibliographically approved

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Bengtsson, LisaKörnich, Heiner
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