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

Related authors

Separating the albedo reducing effect of different light absorbing particles on snow using deep learning
Lou-Anne Chevrollier, Adrien Wehrlé, Joseph M. Cook, Norbert Pirk, Liane G. Benning, Alexandre M. Anesio, and Martyn Tranter
EGUsphere, https://doi.org/10.5194/egusphere-2024-2583,https://doi.org/10.5194/egusphere-2024-2583, 2024
Short summary
Spatio-temporal information propagation using sparse observations in hyper-resolution ensemble-based snow data assimilation
Esteban Alonso-González, Kristoffer Aalstad, Norbert Pirk, Marco Mazzolini, Désirée Treichler, Paul Leclercq, Sebastian Westermann, Juan Ignacio López-Moreno, and Simon Gascoin
Hydrol. Earth Syst. Sci., 27, 4637–4659, https://doi.org/10.5194/hess-27-4637-2023,https://doi.org/10.5194/hess-27-4637-2023, 2023
Short summary
Snow–vegetation–atmosphere interactions in alpine tundra
Norbert Pirk, Kristoffer Aalstad, Yeliz A. Yilmaz, Astrid Vatne, Andrea L. Popp, Peter Horvath, Anders Bryn, Ane Victoria Vollsnes, Sebastian Westermann, Terje Koren Berntsen, Frode Stordal, and Lena Merete Tallaksen
Biogeosciences, 20, 2031–2047, https://doi.org/10.5194/bg-20-2031-2023,https://doi.org/10.5194/bg-20-2031-2023, 2023
Short summary
Understanding wind-driven melt of patchy snow cover
Luuk D. van der Valk, Adriaan J. Teuling, Luc Girod, Norbert Pirk, Robin Stoffer, and Chiel C. van Heerwaarden
The Cryosphere, 16, 4319–4341, https://doi.org/10.5194/tc-16-4319-2022,https://doi.org/10.5194/tc-16-4319-2022, 2022
Short summary
CO2 and CH4 exchanges between moist moss tundra and atmosphere on Kapp Linné, Svalbard
Anders Lindroth, Norbert Pirk, Ingibjörg S. Jónsdóttir, Christian Stiegler, Leif Klemedtsson, and Mats B. Nilsson
Biogeosciences, 19, 3921–3934, https://doi.org/10.5194/bg-19-3921-2022,https://doi.org/10.5194/bg-19-3921-2022, 2022
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
The role of time averaging of eddy covariance fluxes on water use efficiency dynamics of maize
Arun Rao Karimindla, Shweta Kumari, Saipriya S R, Syam Chintala, and BVN P. Kambhammettu​​​​​​​
Atmos. Meas. Tech., 17, 5477–5490, https://doi.org/10.5194/amt-17-5477-2024,https://doi.org/10.5194/amt-17-5477-2024, 2024
Short summary
Number- and size-controlled rainfall regimes in the Netherlands: physical reality or statistical mirage?
Marc Schleiss
Atmos. Meas. Tech., 17, 4789–4802, https://doi.org/10.5194/amt-17-4789-2024,https://doi.org/10.5194/amt-17-4789-2024, 2024
Short summary
The Far-INfrarEd Spectrometer for Surface Emissivity (FINESSE) – Part 2: First measurements of the emissivity of water in the far-infrared
Laura Warwick, Jonathan E. Murray, and Helen Brindley
Atmos. Meas. Tech., 17, 4777–4787, https://doi.org/10.5194/amt-17-4777-2024,https://doi.org/10.5194/amt-17-4777-2024, 2024
Short summary
Bias Correction and Application of Labeled Smartphone Pressure Data for Evaluating the Best Track of Landfalling Tropical Cyclones
Ge Qiao, Yuyao Cao, Qinghong Zhang, and Juanzhen Sun
EGUsphere, https://doi.org/10.5194/egusphere-2024-1505,https://doi.org/10.5194/egusphere-2024-1505, 2024
Short summary
Hailstorm events in the Central Andes of Peru: insights from historical data and radar microphysics
Jairo M. Valdivia, José Luis Flores-Rojas, Josep J. Prado, David Guizado, Elver Villalobos-Puma, Stephany Callañaupa, and Yamina Silva-Vidal
Atmos. Meas. Tech., 17, 2295–2316, https://doi.org/10.5194/amt-17-2295-2024,https://doi.org/10.5194/amt-17-2295-2024, 2024
Short summary

Cited articles

Aalstad, K., Westermann, S., Schuler, T. V., Boike, J., and Bertino, L.: Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites, The Cryosphere, 12, 247–270, https://doi.org/10.5194/tc-12-247-2018, 2018. a, b, c, d, e
Aalstad, K., Westermann, S., and Bertino, L.: Evaluating satellite retrieved fractional snow-covered area at a high-Arctic site using terrestrial photography, Remote Sens. Environ., 239, 111618, https://doi.org/10.1016/j.rse.2019.111618, 2020. a
Alonso-González, E., Gutmann, E., Aalstad, K., Fayad, A., Bouchet, M., and Gascoin, S.: Snowpack dynamics in the Lebanese mountains from quasi-dynamically downscaled ERA5 reanalysis updated by assimilating remotely sensed fractional snow-covered area, Hydrol. Earth Syst. Sci., 25, 4455–4471, https://doi.org/10.5194/hess-25-4455-2021, 2021. a, b
Alonso-González, E., Aalstad, K., Baba, M. W., Revuelto, J., López-Moreno, J. I., Fiddes, J., Essery, R., and Gascoin, S.: MuSA: The Multiscale Snow Data Assimilation System (v1.0), Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2022-137, in review, 2022. a, b
Ardeshiri, H., Cassiani, M., Park, S. Y., Stohl, A., Pisso, I., and Dinger, A. S.: On the Convergence and Capability of the Large-Eddy Simulation of Concentration Fluctuations in Passive Plumes for a Neutral Boundary Layer at Infinite Reynolds Number, Bound.-Lay. Meteorol., 176, 291–327, https://doi.org/10.1007/s10546-020-00537-6, 2020. a
Download
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.