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GEODAR data and the flow regimes of snow avalanches.

Köhler, A. and McElwaine, J. N. and Sovilla, B. (2018) 'GEODAR data and the flow regimes of snow avalanches.', Journal of geophysical research : earth surface., 123 (6). pp. 1272-1294.


GEODAR, a custom radar system, images avalanches over the entire slope with high spatial and temporal resolution at the experimental test‐site Vallée de la Sionne in Switzerland. Between winter seasons 2009/10 and 2014/15, data has been acquired from 77 avalanches. These data sets describe a wide variety of avalanches, which we classify in terms of seven flow regimes and combinations thereof. These flow regimes expand on previous classifications, with four identifiable dense flow regimes (where interaction between granules and with the flow bed dominates dynamics) and two different dilute flow regimes (where interaction between snow particles and the air becomes dominant). There is a further regime identified where snow balls simply roll down the mountain. A cold dense regime and a warm shear regime behave like non‐cohesive granular flows with velocity shear throughout the flow. A sliding slab regime and a warm plug regime occur when cohesion dominates and causes the flow units to act as solid‐like objects sliding on a thin shear zone. An intermittent regime connects the cold dense regime with the suspension regime, and is characterised by highly fluctuating density and surging activity. GEODAR enables localization of these flow regimes and transitions between them in time and space. We discuss flow regime transitions in terms of snow properties, topography, speed and size of the avalanches. This paper also serves as a reference for the data set which is made publicly available and should prove to be an invaluable resource for the development of physically based avalanche models.

Item Type:Article
Full text:(AM) Accepted Manuscript
Available under License - Creative Commons Attribution Non-commercial No Derivatives.
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Full text:(VoR) Version of Record
Available under License - Creative Commons Attribution Non-commercial No Derivatives.
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Publisher statement:© The Authors. This is an open access article under theterms of the Creative CommonsAttribution-NonCommercial-NoDerivsLicense, which permits use anddistribution in any medium, providedthe original work is properly cited, theuse is non-commercial and nomodifications or adaptations are made.
Date accepted:31 October 2017
Date deposited:18 April 2018
Date of first online publication:14 June 2018
Date first made open access:12 July 2018

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