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A stochastic parameterization for deep convection using cellularautomata
Sveriges meteorologiska och hydrologiska institut (SMHI), Norrköping.
(Engelska)Ingår i: Journal of Atmospheric Sciences, ISSN 0022-4928, E-ISSN 1520-0469Artikel i tidskrift (Refereegranskat) Submitted
Nationell ämneskategori
Meteorologi och atmosfärforskning
Forskningsämne
atmosfärvetenskap och oceanografi
Identifikatorer
URN: urn:nbn:se:su:diva-75192OAI: oai:DiVA.org:su-75192DiVA, id: diva2:514970
Tillgänglig från: 2012-04-11 Skapad: 2012-04-11 Senast uppdaterad: 2017-12-07Bibliografiskt granskad
Ingår i avhandling
1. On the Convective-Scale Predictability of the Atmosphere
Öppna denna publikation i ny flik eller fönster >>On the Convective-Scale Predictability of the Atmosphere
2012 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

A well-represented description of convection in weather and climate models is essential since convective clouds strongly influence the climate system. Convective processes interact with radiation, redistribute sensible and latent heat and momentum, and impact hydrological processes through precipitation. Depending on the models’ horizontal resolution, the representation of convection may look very different. However, the convective scales not resolved by the model are traditionally parameterized by an ensemble of non-interacting convective plumes within some area of uniform forcing, representing the “large scale”. A bulk representation of the mass-flux associated with the individual plumes in the defined area provide the statistical effect of moist convection on the atmosphere. Studying the characteristics of the ECMWF ensemble prediction system it is found that the control forecast of the ensemble system is not variable enough in order to yield a sufficient spread using an initial perturbation technique alone. Such insufficient variability may be addressed in the parameterizations of, for instance, cumulus convection where the sub-grid variability in space and time is traditionally neglected. Furthermore, horizontal transport due to gravity waves can act to organize deep convection into larger scale structures which can contribute to an upscale energy cascade. However, horizontal advection and numerical diffusion are the only ways through which adjacent model grid-boxes interact in the models. The impact of flow dependent horizontal diffusion on resolved deep convection is studied, and the organization of convective clusters is found very sensitive to the method of imposing horizontal diffusion. However, using numerical diffusion in order to represent lateral effects is undesirable. To address the above issues, a scheme using cellular automata in order to introduce lateral communication, memory and a stochastic representation of the statistical effects of cumulus convection is implemented in two numerical weather models. The behaviour of the scheme is studied in cases of organized convective squall-lines, and initial model runs show promising improvements.

Ort, förlag, år, upplaga, sidor
Stockholm: Department of Meteorology, Stockholm University, 2012. s. 45
Nyckelord
Cumulus convection, cellular automata, model uncertainty, sub-grid scale processes, numerical weather prediction
Nationell ämneskategori
Meteorologi och atmosfärforskning
Forskningsämne
atmosfärvetenskap och oceanografi
Identifikatorer
urn:nbn:se:su:diva-75195 (URN)978-91-7447-494-7 (ISBN)
Disputation
2012-05-25, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 16 B, Stockholm, 10:00 (Engelska)
Opponent
Handledare
Anmärkning

At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 4: Submitted. 

Tillgänglig från: 2012-05-03 Skapad: 2012-04-11 Senast uppdaterad: 2013-04-10Bibliografiskt granskad

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