Notice bibliographique
Résumé
Abstract. Freshwater, in the form of terrestrial runoff, is hypothesized to have played a critical role in past centennial to millennial scale climate variability by suppressing the production of deep-water in the North Atlantic. It may also play a central role in future climate change as ice sheet and glacier melt accelerates under anthropogenic climate change. In model studies of both past and future climate change, freshwater Hosing (i.e. injection across wide bands in the North Atlantic) is typically used as a means-to-an-end by inducing a strong thermohaline circulation and climate response, with little regard for the other roles that freshwater plays in a complex coupled climate environment. Herein, we evaluate the realism of Hosing relative to two more sophisticated freshwater injection methods, all under glacial boundary conditions: regional injection (allowing the relatively coarse-resolution climate model to transport the freshwater) and a novel freshwater fingerprint method. The latter approach distributes freshwater into an eddy-parametrizing ocean model based upon where it is transported to in a higher resolution eddy-permitting model. Here the COSMOS Earth system model is used as the eddy-parametrizing model, and a configuration of the MITgcm model as the eddy-permitting model. This analysis address three primary questions. Firstly, where is freshwater routed at moderate versus eddy-permitting resolution? Secondly, does the freshwater fingerprint method allow the coarser resolution model to reproduce the net-results of eddy-permitting behaviour? Thirdly, how do climate impacts vary between different forms of freshwater injection? Of the four outlets tested, we find that freshwater released at the Mackenzie River (MAK) outlet results in the most similar freshwater transport patterns at both the eddy-parametrizing and the eddy-permitting resolutions. However at eddy-permitting resolution there is a greater freshening of the contemporary Labrador Sea deep water formation region and mixing of freshwater into the Icelandic Sea. Similarly, Fennoscandian (FEN) freshwater discharge at eddy-permitting resolution results in more freshening of the Greenland-Iceland-Norwegian (GIN) Seas. Freshwater released from within the Gulf of St. Lawrence (GSL) demonstrates large-scale differences between coarse-resolution versus eddy-permitting distributions over the whole North Atlantic. At eddy-permitting resolution, GSL-sourced freshwater freshens the North Atlantic (specifically deep water formation regions important during cold glacial periods) more effectively than at eddy-parametrizing resolution. In COSMOS, freshwater deposited into the GOM results in a larger salinity anomaly at sites of deep-water formation in the northern North Atlantic than freshwater deposited into the GSL, whereas this relationship is reversed in MITgcm. When instead the freshwater fingerprint method is used in COSMOS, the relative strengths of GOM and GSL salinity anomalies in this deep-water formation region align with the eddy-permitting responses. However, for all injection locations considered, the pattern of MITgcm salinity anomalies are best matched by the COSMOS regional injection simulations and not the fingerprint injection simulations. Hosing the North Atlantic in COSMOS results in stronger and earlier sea ice growth and surface cooling versus either regional injection or the fingerprint methods. Comparing regional injections to their respective fingerprint counterparts, injecting freshwater at the outlets results in earlier, but not faster, climate changes in the GIN Seas, mainland Europe, and GRIP ice core regions for the MAK and FEN regions relative to the fingerprint methods. For these injections, regional simulations show both a stronger and faster initial AMOC reduction than the fingerprint simulations. In short, for at least the COSMOS model, both the hosing and fingerprint methodologies are inferior to regional injection when considering salinity distributions alone but when considering AMOC and freshening of deep-water formation regions the fingerprint method corrects the response of the GSL and GOM outlets.
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 | 0,003 | 0,024 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,029 | 0,025 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,149 | 0,116 |
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 ».