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| Titel |
Multifractal properties of embedded convective structures in orographic precipitation: toward subgrid-scale predictability |
| VerfasserIn |
M. Nogueira, A. P. Barros, P. M. A. Miranda |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 20, no. 5 ; Nr. 20, no. 5 (2013-09-11), S.605-620 |
| Datensatznummer |
250086044
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| Publikation (Nr.) |
 copernicus.org/npg-20-605-2013.pdf |
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| Zusammenfassung |
| Rain and cloud fields produced by fully nonlinear idealized cloud resolving
numerical simulations of orographic convective precipitation display
statistical multiscaling behavior, implying that multifractal diagnostics
should provide a physically robust basis for the downscaling and sub-grid
scale parameterizations of moist processes. Our results show that the
horizontal scaling exponent function (and respective multiscaling
parameters) of the simulated rainfall and cloud fields varies with
atmospheric and terrain properties, particularly small-scale terrain
spectra, atmospheric stability, and advective timescale. This implies that
multifractal diagnostics of moist processes for these simulations are
fundamentally transient, exhibiting complex nonlinear behavior depending on
atmospheric conditions and terrain forcing at each location. A particularly
robust behavior found here is the transition of the multifractal parameters
between stable and unstable cases, which has a clear physical correspondence
to the transition from stratiform to organized (banded and cellular)
convective regime. This result is reinforced by a similar behavior in the
horizontal spectral exponent. Finally, our results indicate that although
nonlinearly coupled fields (such as rain and clouds) have different scaling
exponent functions, there are robust relationships with physical
underpinnings between the scaling parameters that can be explored for hybrid
dynamical-statistical downscaling. |
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