Skip to main content

ORIGINAL RESEARCH article

Front. Earth Sci.
Sec. Cryospheric Sciences
Volume 13 - 2025 | doi: 10.3389/feart.2025.1508719

Mapping red algal blooms and their albedo reducing effect on seasonal snowfields at Hardangervidda, Southern Norway

Provisionally accepted
  • 1 Department of Environmental Sciences, Faculty of Technical Sciences, Aarhus University, Roskilde, Capital Region of Denmark, Denmark
  • 2 Department of Geography, Faculty of Mathematics and Natural Sciences, University of Zurich, Zurich, Zürich, Switzerland
  • 3 Department of Geosciences, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Oslo, Norway
  • 4 GFZ German Research Centre for Geosciences, Potsdam, Brandenburg, Germany
  • 5 Department of Earth Sciences, Free University of Berlin, Berlin, Berlin, Germany

The final, formatted version of the article will be published soon.

    Red snow algae bloom at the surface of snowfields worldwide, and their detection is relevant for ecological, biogeochemical and mass balance studies. In this study, we present maps of red snow algae abundance and albedo reducing effect over ∼ 9700 m 2 of seasonal snowfields across Hardangervidda, Southern Norway, in July and August 2023. We co-located RGB imagery acquired with a light-weight Uncrewed Aerial Vehicle (UAV) to 129 hyperspectral reflectance spectra from which the snow surface properties were retrieved, thereby enabling high-resolution aerial mapping of algal properties. The average albedo reducing effect of the algae over the entire area was 0.012 ± 0.005, and attained 0.028 ± 0.004 on a snowfield of ∼ 710 m 2 . Across snow surfaces with visible blooms only, the algal albedo reducing effect was 0.045 ± 0.003, equivalent to an additional ∼ 3 mm of daily melting under local illumination conditions, and aggregating to 5500 ± 2300 kg of daily snowmelt. The intensity and spatial coverage of surface algal blooms were very variable between and within the individual snowfields. Analysis of the UAV imagery suggests that multiple small and distributed samples are at least twice more likely to yield representative estimates of the average snow algal concentration of a snowfield compared to fewer, larger samples. Our study demonstrates the potential of low-cost and easy to deploy UAVs for red snow algal monitoring at the cm to sub-cm scale, which can be used to better understand their spatial ecology and role in albedo reduction.

    Keywords: Snow, albedo, UAV, algae, Blooms

    Received: 09 Oct 2024; Accepted: 21 Jan 2025.

    Copyright: © 2025 Chevrollier, Wehrlé, Cook, Guillet, Benning, Anesio and Tranter. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Lou-Anne Chevrollier, Department of Environmental Sciences, Faculty of Technical Sciences, Aarhus University, Roskilde, 4000, Capital Region of Denmark, Denmark

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.