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| Titel |
Implementation of the Plant-Craig stochastic parameterization of deep moist convection in a numerical atmospheric model |
| VerfasserIn |
Pieter Groenemeijer, George Craig |
| Konferenz |
EGU General Assembly 2010
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 12 (2010) |
| Datensatznummer |
250040166
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| Zusammenfassung |
| We report on our efforts to implement a stochastic scheme for deep moist convection into the COSMO (Consortium for Small-scale Modeling) atmospheric model, and use the scheme in simulations with 7 km grid-spacing.
A parameterization scheme of deep moist convection aims to represent the net effect of convection occurring on sub-grid scales, i.e. that which a model cannot resolve explicitly. Given properties of the resolved flow, it produces a feedback to that resolved scale flow. A stochastic parameterization, like the Plant-Craig (PC) scheme, takes into account the fact that the unresolved convection is not merely determined by resolved-scale parameters, but also by unresolved physics. To this aim, the PC-scheme, being based on equilibrium statistics, uses convective plumes that are randomly drawn from a probability density function that describe the chance of launching a plume with a certain mass flux.
Preliminary results show a more realistic distribution of convective precipitation than that produced by non-stochastic schemes. Statistical properties of the scheme's convective precipitation are compared with those observed by radar and those of non-stochastic schemes. |
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