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Can Weather Radars Be Used to Estimate Snow Accumulation on Alpine Glaciers? An Evaluation Based on Glaciological Surveys

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  • 1 Department of Geosciences, University of Fribourg, Fribourg, Switzerland
  • 2 Radar, Satellite, and Nowcasting Department, MeteoSwiss, Locarno-Monti, Switzerland
  • 3 Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
  • 4 Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
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Abstract

The snow water equivalent (SWE) is a key component for understanding changes in the cryosphere in high mountain regions. Yet, a reliable quantification at a high spatiotemporal resolution remains challenging in such environments. In this study, we investigate the potential of an operational weather radar–rain gauge composite (CombiPrecip) to infer the daily evolution of SWE on seven Swiss glaciers. To this end, we validate cumulative CombiPrecip estimates with glacier-wide manual SWE observations (snow probing, snow pits) obtained around the time of the seasonal peak during four winter seasons (2015–19). CombiPrecip underestimates the end-of-season snow accumulation by factors of 2.2 up to 3.7, depending on the glacier site. These factors are consistent over the four winter seasons. The regional variability can be mainly attributed to the empirical visibility of the Swiss radar network within the Alps. To account for the underestimation, we investigate three approaches to adjust CombiPrecip for the applicability to glacier sites. Thereby, we combine the factor of underestimation with a precipitation-phase parameterization. For further comparison, we apply a rain gauge catch-efficiency function based on wind speed. We validate these approaches with 14 manual point observations of SWE obtained on two glaciers during three winter seasons. All approaches show a similar improvement of CombiPrecip estimates. We conclude that CombiPrecip has great potential to estimate SWE on glaciers at a high temporal resolution, but further investigations are necessary to understand the regional variability of the bias throughout the Swiss Alps.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JHM-D-20-0112.s1.

Corresponding author: Rebecca Gugerli, rebecca.gugerli@unifr.ch

Abstract

The snow water equivalent (SWE) is a key component for understanding changes in the cryosphere in high mountain regions. Yet, a reliable quantification at a high spatiotemporal resolution remains challenging in such environments. In this study, we investigate the potential of an operational weather radar–rain gauge composite (CombiPrecip) to infer the daily evolution of SWE on seven Swiss glaciers. To this end, we validate cumulative CombiPrecip estimates with glacier-wide manual SWE observations (snow probing, snow pits) obtained around the time of the seasonal peak during four winter seasons (2015–19). CombiPrecip underestimates the end-of-season snow accumulation by factors of 2.2 up to 3.7, depending on the glacier site. These factors are consistent over the four winter seasons. The regional variability can be mainly attributed to the empirical visibility of the Swiss radar network within the Alps. To account for the underestimation, we investigate three approaches to adjust CombiPrecip for the applicability to glacier sites. Thereby, we combine the factor of underestimation with a precipitation-phase parameterization. For further comparison, we apply a rain gauge catch-efficiency function based on wind speed. We validate these approaches with 14 manual point observations of SWE obtained on two glaciers during three winter seasons. All approaches show a similar improvement of CombiPrecip estimates. We conclude that CombiPrecip has great potential to estimate SWE on glaciers at a high temporal resolution, but further investigations are necessary to understand the regional variability of the bias throughout the Swiss Alps.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JHM-D-20-0112.s1.

Corresponding author: Rebecca Gugerli, rebecca.gugerli@unifr.ch

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