Inferring surface energy fluxes using drone data assimilation in large eddy simulations

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Abstract 12 - 2 37 - 2 46 - 2 12 18 37 - 2 52 - 2 58 - 2 0.90 0.40 0.83 (H+LE). While this comparison uses the simplifying assumptions of flux homogeneity, stationarity, and flat terrain, it is emphasized that the drone data assimilation framework is not confined to these assumptions and can thus readily be extended to more complex cases and other scalar fluxes, such as for trace gases in future studies.

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Bibliographic citation: Inferring surface energy fluxes using drone data assimilation in large eddy simulations ; volume:15 ; number:24 ; year:2022 ; pages:7293-7314 ; extent:22
Atmospheric measurement techniques ; 15, Heft 24 (2022), 7293-7314 (gesamt 22)

Creator: Pirk, Norbert
Aalstad, Kristoffer
Westermann, Sebastian
Vatne, Astrid
van Hove, Alouette
Tallaksen, Lena M.
Cassiani, Massimo
Katul, Gabriel

DOI: 10.5194/amt-15-7293-2022

URN: urn:nbn:de:101:1-2022122204225561282997

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:30 AM CEST

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Pirk, Norbert
Aalstad, Kristoffer
Westermann, Sebastian
Vatne, Astrid
van Hove, Alouette
Tallaksen, Lena M.
Cassiani, Massimo
Katul, Gabriel

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Inferring surface energy fluxes using drone data assimilation in large eddy simulations

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Other Objects (12)

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