Back
Full-text
Journal article

Snow depth variability in the Northern Hemisphere mountains observed from space.

  • Lievens H Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium. hans.lievens@kuleuven.be.
  • Demuzere M Laboratory of Hydrology and Water Management, Ghent University, Ghent, Belgium.
  • Marshall HP Department of Geosciences, Boise State University, Boise, ID, USA.
  • Reichle RH NASA Goddard Space Flight Center, Greenbelt, MD, USA.
  • Brucker L NASA Goddard Space Flight Center, Greenbelt, MD, USA.
  • Brangers I Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium.
  • de Rosnay P European Centre for Medium-Range Weather Forecasts, Reading, UK.
  • Dumont M Université Grenoble Alpes, Université de Toulouse, Météo-France, Grenoble, France, CNRS, CNRM, Centre d'Etudes de la Neige, Grenoble, France.
  • Girotto M NASA Goddard Space Flight Center, Greenbelt, MD, USA.
  • Immerzeel WW Department of Physical Geography, Utrecht University, Utrecht, The Netherlands.
  • Jonas T WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland.
  • Kim EJ NASA Goddard Space Flight Center, Greenbelt, MD, USA.
  • Koch I International Centre for Integrated Mountain Development, Kathmandu, Nepal.
  • Marty C WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland.
  • Saloranta T Hydrology Department, Norwegian Water Resources and Energy Directorate NVE, Oslo, Norway.
  • Schöber J TIWAG, Tiroler Wasserkraft AG, Innsbruck, Austria.
  • De Lannoy GJM Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium.
Show more…
  • 2019-10-13
Published in:
  • Nature communications. - 2019
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy
General Chemistry
English Accurate snow depth observations are critical to assess water resources. More than a billion people rely on water from snow, most of which originates in the Northern Hemisphere mountain ranges. Yet, remote sensing observations of mountain snow depth are still lacking at the large scale. Here, we show the ability of Sentinel-1 to map snow depth in the Northern Hemisphere mountains at 1 km² resolution using an empirical change detection approach. An evaluation with measurements from ~4000 sites and reanalysis data demonstrates that the Sentinel-1 retrievals capture the spatial variability between and within mountain ranges, as well as their inter-annual differences. This is showcased with the contrasting snow depths between 2017 and 2018 in the US Sierra Nevada and European Alps. With Sentinel-1 continuity ensured until 2030 and likely beyond, these findings lay a foundation for quantifying the long-term vulnerability of mountain snow-water resources to climate change.
Language
  • English
Open access status
gold
Identifiers
Persistent URL
https://sonar.ch/global/documents/112342
Statistics
Document views: 53 File downloads:
  • Full-text: 0