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| Titel |
A refined cloud parameterization based on double-Gaussian probability density functions |
| VerfasserIn |
Ann Kristin Naumann, Axel Seifert, Juan Pedro Mellado |
| Konferenz |
EGU General Assembly 2013
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250076289
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| Zusammenfassung |
| The choice of the cloud parameterization in a large scale model like a numerical
weather prediction model or a global circulation model is known to have a large
impact on microphysical and radiative processes which in turn determine, e.g., the
formation of precipitation or the energy balance. Cloud properties like cloud fraction
and average liquid water in a large scale model grid box depend on the subgrid
variability of temperature and moisture as characterized by their probability density
function (PDF). Therefore PDF-based parameterizations of boundary layer clouds are
often used in numerical weather prediction or global circulation models. In recent
years closures using a 5-parameter double-Gaussian PDF have become increasingly
popular because the double-Gaussian distribution can provide very accurate fits
to observed or simulated empirical PDFs. Even if we assume that the first three
moments of the subgrid PDF can be predicted in the large scale model, the number of
parameters still has to be reduced from five to three, i.e., two closure equations are
necessary.
Considering cases of different cloud regimes, i.e., trade wind cumulus, stratocumulus and
stratocumulus-to-cumulus transition, from large-eddy simulations as well as direct
numerical simulations and observational data, a new parameterization based on
double-Gaussian PDFs is proposed. A priori testing in large-eddy simulations suggests
that the reduced 3-parameter double-Gaussian is an appropriate approximation,
especially when the differences between stratocumulus and shallow convection
are taken into account. In contrast to previous work, we do not find a perfectly
anti-symmetric shape of negatively and positively skewed subgrid PDFs. Instead the
PDFs differ in the shape of their tails, with the tail of a positively skewed PDF in a
shallow cumulus regime being heavier than the tail of a negatively skewed PDF in a
stratocumulus regime. This is consistent with the physical understanding that cloudy
updrafts in shallow cumulus are more vigorous than non-cloudy downdrafts in
stratocumulus. When taking this difference into account in the closure equations, the
new parameterization is able to reproduce profiles of cloud fraction and average
liquid water properly. Additionally, we show that the error of the parameterization
is smallest for a horizontal resolution of 5 – 20 km and also depends on whether
of not the cloud field self-organizes, e.g., in cloud clusters and mesoscale arcs. |
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