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A stochastic parametrization for deep convection using cellular automata
SMHI, Research Department, Meteorology.ORCID iD: 0000-0001-8756-0331
2013 (English)In: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 139, no 675, 1533-1543 p.Article in journal (Refereed) Published
Abstract [en]

A cellular automaton (CA) is introduced to the deep convection parametrization of the high-resolution limited-area model Aire Limitee Adaptation/Application de la Recherche a l'Operationnel (ALARO). The self-organizational characteristics of the CA allow for lateral communication between adjacent numerical weather prediction (NWP) model grid boxes and add additional memory to the deep convection scheme. The CA acts in two horizontal dimensions, with finer grid spacing than the NWP model. It is randomly seeded in regions where convective available potential energy (CAPE) exceeds a threshold value. Both deterministic and probabilistic rules, coupled to the large-scale wind, are explored to evolve the CA in time. Case studies indicate that the scheme has the potential to organize cells along convective squall lines and enhance advective effects. An ensemble of forecasts using the present CA scheme demonstrated an ensemble spread in the resolved wind field in regions where deep convection is large. Such a spread represents the uncertainty due to subgrid variability of deep convection and could be an interesting addition to an ensemble prediction system.

Place, publisher, year, edition, pages
2013. Vol. 139, no 675, 1533-1543 p.
Keyword [en]
mesoscale modelling, stochastic physics, deep convection parametrization
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
URN: urn:nbn:se:smhi:diva-362DOI: 10.1002/qj.2108ISI: 000324390000010OAI: oai:DiVA.org:smhi-362DiVA: diva2:802008
Available from: 2015-04-10 Created: 2015-03-31 Last updated: 2017-12-04Bibliographically approved

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Bengtsson, Lisa

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