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Status: Bibliographieeintrag

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Verfasst von:Bessac, Julie [VerfasserIn]   i
 Christensen, Hannah M. [VerfasserIn]   i
 Endo, Kota [VerfasserIn]   i
 Monahan, Adam H. [VerfasserIn]   i
 Weitzel, Nils [VerfasserIn]   i
Titel:Scale-aware space-time stochastic parameterization of subgrid-scale velocity enhancement of sea surface fluxes
Verf.angabe:Julie Bessac, Hannah M. Christensen, Kota Endo, Adam H. Monahan, and Nils Weitzel
E-Jahr:2021
Jahr:26 April 2021
Umfang:23 S.
Fussnoten:Gesehen am 28.06.2021
Titel Quelle:Enthalten in: Journal of advances in modeling earth systems
Ort Quelle:Fort Collins, Colo., 2009
Jahr Quelle:2021
Band/Heft Quelle:13(2021), 4, Artikel-ID e2020MS002367, Seite 1-23
ISSN Quelle:1942-2466
Abstract:Stochastic representation of the influence of the subgrid-scales on the resolved scales in weather and climate models has been shown to improve ensemble spread and resolved variability. We propose a statistical scale-aware space-time model to characterize the contribution of mesoscale wind variability to air-sea exchanges. In an earlier study, we analyzed the difference between “true” fluxes computed from a high resolution simulation and “resolved” fluxes obtained by coarse graining. This discrepancy is modeled in space and time, conditioned on the coarse-grained wind and precipitation fields, to parameterize the enhancement of fluxes by mesoscale velocity variations. Stochastic parameterization models have traditionally been developed for particular model resolutions without the explicit capability to adapt to model resolution. We present an approach to develop stochastic models that adapt to resolution in a scale-aware fashion. The scale-aware parameterization is developed from empirical results for systematically coarse-grained high-resolution numerical model output. The statistical model is fit from numerical model output at three different coarsening resolutions. From this scale-aware parameterization, we derive a stochastic parameterization of flux enhancement by subgrid velocity variations for arbitrary resolutions and characterize the conditional distributions and space-time structures of the flux enhancement across model resolutions.
DOI:doi:10.1029/2020MS002367
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext ; Verlag: https://doi.org/10.1029/2020MS002367
 Volltext: https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2020MS002367
 DOI: https://doi.org/10.1029/2020MS002367
Datenträger:Online-Ressource
Sprache:eng
K10plus-PPN:1761323075
Verknüpfungen:→ Zeitschrift

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