Articles | Volume 15, issue 24
https://doi.org/10.5194/amt-15-7293-2022
https://doi.org/10.5194/amt-15-7293-2022
Research article
 | 
20 Dec 2022
Research article |  | 20 Dec 2022

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

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

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Latest update: 24 Apr 2024
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Short summary
In this study, we show how sparse and noisy drone measurements can be combined with an ensemble of turbulence-resolving wind simulations to estimate uncertainty-aware surface energy exchange. We demonstrate the feasibility of this drone data assimilation framework in a series of synthetic and real-world experiments. This new framework can, in future, be applied to estimate energy and gas exchange in heterogeneous landscapes more representatively than conventional methods.