Suche nach Personen

plus im Publikationsserver
plus bei BASE
plus bei Google Scholar

Daten exportieren

 

Variational balance models for the three-dimensional Euler–Boussinesq equations with full Coriolis force

Titelangaben

Verfügbarkeit überprüfen

Özden, Gözde ; Oliver, Marcel:
Variational balance models for the three-dimensional Euler–Boussinesq equations with full Coriolis force.
In: Physics of fluids. 33 (2021) 7: 076606. - 15 S.
ISSN 1089-7666 ; 1070-6631

Volltext

Volltext Link zum Volltext (externe URL):
https://doi.org/10.1063/5.0053092

Kurzfassung/Abstract

We derive a semi-geostrophic variational balance model for the three-dimensional Euler–Boussinesq equations on the nontraditional f-plane under the rigid lid approximation. The model is obtained by a small Rossby number expansion in the Hamilton principle, with no other approximations made. We allow for a fully non-hydrostatic flow and do not neglect the horizontal components of the Coriolis parameter; that is, we do not make the so-called “traditional approximation.” The resulting balance models have the same structure as the “L1 balance model” for the primitive equations: a kinematic balance relation, the prognostic equation for the three-dimensional tracer field, and an additional prognostic equation for a scalar field over the two-dimensional horizontal domain, which is linked to the undetermined constant of integration in the thermal wind relation. The balance relation is elliptic under the assumption of stable stratification and sufficiently small fluctuations in all prognostic fields.
ACKNOWLEDGMENTS
This paper is a contribution to project M2 (Systematic Multi-Scale Analysis and Modeling for Geophysical Flow) of the Collaborative Research Center TRR 181 “Energy Transfers in Atmosphere and Ocean” funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Project No. 274762653. Additional funding was received through the Ideen-und Risikofund 2020 at Universität Hamburg.

Weitere Angaben

Publikationsform:Artikel
Sprache des Eintrags:Englisch
Institutionen der Universität:Mathematisch-Geographische Fakultät > Mathematik > Lehrstuhl für Mathematik - Angewandte Mathematik
Mathematisch-Geographische Fakultät > Mathematik > Mathematisches Institut für Maschinelles Lernen und Data Science (MIDS)
DOI / URN / ID:10.1063/5.0053092
Open Access: Freie Zugänglichkeit des Volltexts?:Nein
Peer-Review-Journal:Ja
Verlag:American Institute of Physics
Die Zeitschrift ist nachgewiesen in:
Titel an der KU entstanden:Nein
KU.edoc-ID:30007
Eingestellt am: 21. Apr 2022 09:46
Letzte Änderung: 07. Jun 2023 10:41
URL zu dieser Anzeige: https://edoc.ku.de/id/eprint/30007/
AnalyticsGoogle Scholar