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Record W30814725 · doi:10.1038/d41586-019-00663-3

Snow Cornice Development and Failure Monitoring

2006· article· en· W30814725 on OpenAlexaboutno aff
Robert A. Burrows, D. M. McClung

Bibliographic record

VenueProceedings of the 2006 International Snow Science Workshop, Telluride, Colorado · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
Fundersnot available
KeywordsSnowGeologyFracture (geology)GeomorphologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Snow cornices are significant winter alpine and snow avalanche hazards. A cornice is a leeward growing mass of snow overhanging from a ridge or sharp break in slope (perpendicular to the ridgeline) due to windblown snow (Seligman, 1936). A cornice’s usual topographic position and cantilevered slab structure, regularly above large avalanche prone slopes, makes cornices crucial to consider from a risk perspective. Although cornices are extensively controlled in avalanche operations, they have been given little attention in science. Only basic work has been done on their formation, development, structure and control, with limited focus and geographic extent (Kobayashi, 1988, McCarty et al., 1986, McClung and Schaerer, 1993, Montagne et al., 1968). Although significant work has been done on snow slab fracture mechanics, no work has been done on cornice failure and fracture mechanics. Three meteorologically-related triggers of cornice failure have been recognized: 1. Snow loading of the cornice overhang during storm and wind events; 2. abrupt temperature changes at the surfaces of the cornice due to a) abrupt warming or cooling air temperatures, b) rain-on-snow events, c) heating by solar radiation; and 3. seasonal warming/prolonged midwinter warm periods. Failure from snow loading results when newly fallen or wind-blown snow accumulates on the cornice overhang at a rate that induces stresses that exceed the strength/fracture toughness of the cornice. Creep fracture is thought to be the primary mechanism for failure of this type. Rain-on-snow events (and the concurrent abrupt warming) on dry snow slabs are shown to immediately increase the creep rate in the surface layer of the snow slab resulting in decreased slab stability (Conway, 1998). This immediate effect may similarly influence cornice stability, as well as the delayed time effects of increased loading from rainfall and weakening due to longer-term warming. Abrupt changes in air temperature alone are thought to be a trigger of dry snow slab avalanches (McClung, 1996). Further circumstantial and anecdotal evidence suggests that cooling and warming of the snow surface from abrupt changes in air temperature and heating from solar radiation initiate slab avalanches and cornice failures. I intend to monitor the development, physical properties (dimensions/geometry, structure, densities), fracture, and failure of a study cornice along with meteorological parameters on a ridge near Kootenay Pass, BC during two winter seasons. Monitoring the three-dimensional time-lapse development of the cornice will be achieved using periodic photography and terrestrial photogrammetry methods (Eos Systems Inc., 2004). Deformation and temperature inside the cornice will be measured using glide shoe-type instrument packages (Conway, 1998). These measurements will include linear displacement, tilt, and snow temperature. A nearby weather station will monitor air temperature, relative humidity, wind, snow depth, and radiation. The goal is to develop a numerical model based on these data in order to quantify and predict cornice deformation and failure. REFERENCES Conway, H., 1998: The impact of surface perturbations on snow-slope stability. Ann. Glac., 26, 307-312. Eos Systems, Inc, 2004: PhotoModeler Pro5 User Manual. Eos Systems, Inc., 500 pp. Kobayashi, D., 1988: Formation process and direction distribution of snow cornices. Cold Reg, Sci. and Tech., 15(2), 131. Latham, J. and J. Montagne, 1970: The possible importance of electrical forces in the development of snow cornices. J.Glac., 9(57), 375-384. McCarty, D., R. L. Brown and J. Montagne, 1986: Cornices: Their growth, properties, and control. Proceedings of the International Snow Science Workshop, Lake Tahoe, CA, ISSW Workshop Committee, 41-45. McClung, 1979: In-situ estimates of the tensile strength of snow utilizing large sample sizes. J. Glac, 22(87), 321. McClung D. M. and P. A. Schaerer, 1993: The Avalanche Handbook, The Mountaineers. 272 pp., McClung, D.M., 1996: Effects of temperature on fractures in dry slab avalanche release. J. Geophys. Res. B, 101(B10), 21907-21920. * Corresponding author address: Robert A. Burrows, Avalanche Research Group, Department of Geography, University of British Columbia, 1984 West Mall, Vancouver, BC Canada V6T 1Z2; tel: 604-518-9664; fax: 604822-6150; email: moraineboy@hotmail.com

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.217
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2006
Admission routes1
Has abstractyes

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