Geostatistical methods for improved quantification of ice mass bed topography
Notice bibliographique
Résumé
Contribution to global mean sea level rise by ice sheets, ice caps and glaciers is accelerating. The total volume of water stored globally in terrestrial ice is estimated by a multitude of methods but principally by the interpolation of icethickness data. For the ice sheets and large Arctic ice caps, ice thickness is predominantly measured by airborne radio-echo sounding surveys which use radio waves to detect the bed of the surveyed ice mass. While such surveys are now extensive, large portions of ice masses are generally unsurveyed due to their size. In order to quantify ice thickness and subsequently ice volume over the entirety of an ice mass, interpolation of the input measurements is used. Throughout this whole process, uncertainties arise. Initially, from the radio-echo sounding (RES) survey and subsequently, in the interpolation. Compounding this is the absence of ground-truthing for measurements and interpolations due to the inaccessibility of ice mass beds. Hence, there is a requirement to find alternative means of quantifying uncertainty in ice thickness measurements and subsequently derived bed topography, and analyses made from these data to reduce the uncertainty in sea level change projections. This thesis develops and applies methods which aim to reduce uncertainty in ice thickness and bed topography datasets. Using high-resolution elevation data, this study exploits the likely similarity between currently ice-covered topography and formerly glaciated topography in the Arctic to generate datasets which provide alternative validation for ice mass bed topography. For the first time topographic error in RES surveying is quantified and corrections are formulated for treating future and historic ice thickness and bed topography data. Additionally, the propagation of these uncertainties through interpolations of bed topography is quantified and reduced, focussing on the Greenland Ice Sheet. Finally, the full suite of methods is applied to ice caps in the Canadian Arctic to generate, for the first time, ice cap wide topography for ice caps in the region that hold approximately a third of the freshwater outside of the continental ice sheets. By quantifying and reducing uncertainty in datasets of bed topography and ice thickness this thesis assesses the perceived stability of the continental ice sheets and large ice Arctic ice caps. From this, the implications of this for near and far term global mean sea-level rise are investigated.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,042 | 0,000 |
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 tête enseignante, 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 ».