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Record W4235995785 · doi:10.5194/tc-2019-56

Optimization of over-summer snow storage at mid-latitude and low elevation

2019· preprint· en· W4235995785 on OpenAlexaboutno aff
Hannah Weiss, Paul R. Bierman, Yves Dubief, Scott D. Hamshaw

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
Fundersnot available
KeywordsSnowSnowmeltEnvironmental scienceElevation (ballistics)Snow fieldLatitudeFirnAtmospheric sciencesClimate changeWind speedSnowpackWater equivalentClimatologyHydrology (agriculture)Snow coverMeteorologyGeologyGeography

Abstract

fetched live from OpenAlex

Abstract. Climate change, including warmer winter temperatures, a shortened snowfall season, and more rain-on-snow events, threatens nordic skiing as a sport. In response, over-summer snow storage, attempted primarily using wood chip insulation, has been successfully employed as a climate change adaptation strategy by high elevation and/or high latitude ski centers in Europe and Canada. Such storage has never been attempted at low-elevation, mid-latitude sites nor have studies quantified snowmelt rate through the summer or correlated snow melt rate with environmental characteristics including ground and air temperature, humidity, wind, and solar radiation. Such data, along with tests of different insulation strategies, are needed to optimize snow storage strategies. Here, we assess the melt rates of two snow piles (each ~ 200 m3) emplaced during spring 2018 in Craftsbury, Vermont (45° N and 360 m asl). We monitored volume change over the melt season using terrestrial laser scanning. We continually logged air-to-snow temperature gradients under different insulating layers including rigid foam, open cell foam, and wood chips both with and without an underlying insulating blanket and an overlying reflective cover. We also measured ground temperatures to a meter depth both under and adjacent to the snow piles and used a snow tube to measure snow density. Snow volume of the two piles changed similarly over the summer, with minimum rates of change (−0.29 m3 day-1 and −0.88 m3 day-1) in September and maximum volumetric loss rates in July of −1.98 m3 day-1 and −2.81 m3 day-1. Snow density changed little over time indicating that most volume reduction was the result of melting. Wet wood chips underlain by an insulating blanket and covered with a reflective cover was the most effective combination for minimizing melt, likely because the surface reflected incoming shortwave radiation while the wet wood chips provided significant thermal mass, allowing much of the energy absorbed during the day to be lost as blackbody radiation at night. Together, the data we collected demonstrate the feasibility of over-summer snow storage even at mid latitudes and low altitudes and suggest efficient insulation strategies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.228
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2019
Admission routes1
Has abstractyes

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