Notice bibliographique
Résumé
Advances in alpine snow and ice hydrology have occurred due to the relentless efforts of field researchers to study snow processes in remote research sites, improvements in automated instrumentation, advances in remote sensing, and improvements in numerical modelling. Crucial has been the joint consideration of the mass and energy conservation equations and phase change in various calculation procedures. For instance, energy budget snowmelt and icemelt methods have replaced calibrated, anti-physical and highly uncertain temperature index melt models. Slope, aspect, remote shading, katabatic flow and wind flow over complex terrain are considered in energy and mass balance calculations. Albedo decay considers changes in grain size and increasingly addresses deposition of impurities such as soot. Snow redistribution by wind and by gravity have been recognized as important processes controlling snow accumulation. Blowing snow redistribution has advanced from flat-earth physics to 3-D complex terrain representations of saltation and suspension transport and sublimation due to turbulent transfer with blowing snow particles. Snow redistribution by forest canopies considers the role of canopy structure in interception and of the competing processes of unloading, sublimation and melt in ablating canopy snow. Snow-soil interactions consider the role of freezing soils on heat flow to snow and infiltration of snowmelt. Snow depth can be measured by LiDAR from planes and drones and snow-covered area and albedo estimated by satellite.However, several challenges remain unsolved or very uncertain. Advection of latent and sensible heat from bare ground or open water to snow or ice is not fully understood in complex terrain. Ice ablation from glaciers terminating in proglacial lakes is uncertain. Alpine blowing snow calculations do not fully consider the role of terrain roughness and sparse vegetation on transport fluxes and atmospheric exchanges. Wind flow calculations in steep alpine terrain are still problematic and incapable of reliable estimation of wind speed and direction. Intercepted snow calculations lack an understanding of wind erosion and redistribution from forest canopies. Snow avalanche calculations used in hydrology are highly empirical and tuned to regional observations, so lack the flexibility and global robustness of physically based methods. Snow water equivalent observations still depend on gravimetric methods and lack reliable high resolution remote sensing approaches. Snowfall measurements are too sparse and in wind swept terrain are still highly uncertain due to wind-induced undercatch and other gauge errors. Albedo impacts from atmospheric deposition on snow and ice and biological magnifiers such as snow and ice algae are understood but not incorporated in calculations. The role of edge effects such as treelines, glacier edges, canopy gaps and ridges on upscaled hydrological responses are incompletely understood. And the full understanding of what fine-scale processes are emergent or are compensated for in larger scale energy and water budget calculations is still being developed.This talk considers the advances in and the prospects for improving snow and ice process understanding, parameterisation and prediction in alpine catchments and calls for new research to solve the remaining uncertainties.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,006 | 0,006 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».