30 Sep 2021
30 Sep 2021
Status: a revised version of this preprint is currently under review for the journal TC.

Review Article: Global Monitoring of Snow Water Equivalent using High Frequency Radar Remote Sensing

Leung Tsang1, Michael Durand2, Chris Derksen3, Ana P. Barros4, Do-Hyuk Kang5, Hans Lievens6, Hans-Peter Marshall7, Jiyue Zhu1, Joel Johnson8, Joshua King3, Juha Lemmetyinen9, Melody Sandells10, Nick Rutter10, Paul Siqueira11, Anne Nolin12, Batu Osmanoglu13, Carrie Vuyovich13, Edward J. Kim13, Drew Taylor14, Ioanna Merkouriadi9, Ludovic Brucker13, Mahdi Navari13, Marie Dumont15, Richard Kelly16, Rhae Sung Kim13, Tien-Hao Liao17, and Xiaolan Xu17 Leung Tsang et al.
  • 1Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, 48109, USA
  • 2School of Earth Sciences & Byrd Polar and Climate Research Center, The Ohio State University, Columbus, OH, 43210, USA
  • 3Climate Research Division, Environment and Climate Change Canada, Toronto, Canada
  • 4Civil and Environmental Engineering University of Illinois at Urbana-Champaign, Urbana, IL, USA
  • 5ESSIC, University of Maryland, College Park, MD, 20740, USA
  • 6Division of Soil and Water Management, KU Leuven, Leuven, Belgium
  • 7Department of Geoscience, Boise State University, Boise, Idaho, USA
  • 8Department of Electrical and Computer Engineering, Ohio State University, Columbus, OH 43212 USA
  • 9Arctic Research Centre, Finnish Meteorological Institute, Helsinki, Finland
  • 10Geography and Environmental Sciences, Northumbria University, Newcastle, UK
  • 11Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
  • 12Department of Geography, University of Nevada-Reno, Reno, NV, USA
  • 13NASA Goddard Space Flight Center, Greenbelt, MD, USA
  • 14Remote Sensing Center, University of Alabama, Tuscaloosa, AL, USA
  • 15Centre d'Etudes de la Neige, Meteo-France, Grenoble, France
  • 16Department of Geography and Environmental Management, University of Waterloo, Waterloo, Canada
  • 17NASA Jet Propulsion Laboratory, Pasadena, CA, USA

Abstract. Seasonal snow cover is the largest single component of the cryosphere in areal extent, covering an average of 46 million square km of Earth's surface (31 % of the land area) each year, and is thus an important expression of and driver of the Earth’s climate. In recent years, Northern Hemisphere spring snow cover has been declining at about the same rate (~ −13 %/decade) as Arctic summer sea ice. More than one-sixth of the world’s population relies on seasonal snowpack and glaciers for a water supply that is likely to decrease this century. Snow is also a critical component of Earth’s cold regions' ecosystems, in which wildlife, vegetation, and snow are strongly interconnected. Snow water equivalent (SWE) describes the quantity of snow stored on the land surface and is of fundamental importance to water, energy, and geochemical cycles. Quality global SWE estimates are lacking. Given the vast seasonal extent combined with the spatially variable nature of snow distribution at regional and local scales, surface observations will not be able to provide sufficient SWE information. Satellite observations presently cannot provide SWE information at the spatial and temporal resolutions required to address science and high socio-economic value applications such as water resource management and streamflow forecasting. In this paper, we review the potential contribution of X- and Ku-Band Synthetic Aperture Radar (SAR) for global monitoring of SWE. We describe radar interactions with snow-covered landscapes, characterization of snowpack properties using radar measurements, and refinement of retrieval algorithms via synergy with other microwave remote sensing approaches. SAR can image the surface during both day and night regardless of cloud cover, allowing high-frequency revisit at high spatial resolution as demonstrated by missions such as Sentinel-1. The physical basis for estimating SWE from X- and Ku-band radar measurements at local scales is volume scattering by millimetre-scale snow grains. Inference of global snow properties from SAR requires an interdisciplinary approach based on field observations of snow microstructure, physical snow modelling, electromagnetic theory, and retrieval strategies over a range of scales. New field measurement capabilities have enabled significant advances in understanding snow microstructure such as grain size, densities, and layering. We describe radar interactions with snow-covered landscapes, the characterization of snowpack properties using radar measurements, and the refinement of retrieval algorithms via synergy with other microwave remote sensing approaches. This review serves to inform the broader snow research, monitoring, and applications communities on progress made in recent decades, and sets the stage for a new era in SWE remote-sensing from SAR measurements.

Leung Tsang et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2021-295', Anonymous Referee #1, 09 Oct 2021
    • AC1: 'Reply on RC1', Leung Tsang, 02 Feb 2022
  • RC2: 'Comment on tc-2021-295', Helmut Rott, 03 Nov 2021
    • AC2: 'Reply on RC2', Leung Tsang, 02 Feb 2022

Leung Tsang et al.

Leung Tsang et al.


Total article views: 1,209 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
822 361 26 1,209 18 21
  • HTML: 822
  • PDF: 361
  • XML: 26
  • Total: 1,209
  • BibTeX: 18
  • EndNote: 21
Views and downloads (calculated since 30 Sep 2021)
Cumulative views and downloads (calculated since 30 Sep 2021)

Viewed (geographical distribution)

Total article views: 1,155 (including HTML, PDF, and XML) Thereof 1,155 with geography defined and 0 with unknown origin.
Country # Views %
  • 1


Latest update: 22 May 2022
Short summary
Snow water equivalent (SWE) is of fundamental importance to water, energy, and geochemical cycles, but is poorly observed globally. Synthetic aperture radar (SAR) measurements at X and Ku-band can address this gap. This review will serve to inform the broad snow research, monitoring, and applications communities on the progress made in recent decades to move towards a new satellite mission capable of addressing the needs of the geoscience researchers and users.