Modeling Long-Term Changes in Climate, Ice Sheets and Sea Level: Using the Paleo Record to Understand Possibilities for the Future
Notice bibliographique
Résumé
The paleoclimate record highlights the susceptibility of ice sheets and sea level to increased global temperatures, even for global warming much less severe than that predicted for future climate. The critical role of climate feedbacks in regulating ice sheets over centuries and millennia highlights the need to use coupled ice-sheet/climate models in assessments of past and future sea level rise. However, coupled climate models are only beginning to include dynamic ice sheets, coupling mechanisms between ice sheets and climate, and the spatial resolution needed to properly simulate the coupled ice-sheet/climate system. During this project, we completed the development and testing of the infrastructure for coupled CESM2-CISM2 paleo-simulations of the Greenland ice sheet. The Community Earth System Model (CESM) is a fully coupled, global climate model that provides state-of-the-art computer simulations of the Earth's past, present, and future climate states. The newest version, CESM2, contributed simulations to the Coupled Model Intercomparison Project Phase 6 (CMIP6). The ice sheet component of CESM2 is the Community Ice Sheet Model Version 2.1 (CESM2.1), a parallel, scalable code with a suite of higher-order ice-flow solvers that are physically realistic for all parts of an ice sheet, including fast-flowing ice streams and outlet glaciers. The incorporation of a physically based “pseudo-plastic” basal sliding scheme gives realistic velocities over most of the Greenland ice sheet, while allowing basal conditions to evolve on multi-century time scales. Additional processes and feedbacks important for long, coupled, millennial-scale simulations – evolving topography, orbital acceleration, asynchronous coupling to dynamic vegetation – have been implemented. The preindustrial ice sheet/Earth system state is achieved via a new, efficient, interactive spin-up method and provides initial conditions for transient paleo-simulations with CESM2-CISM2, as well as the ISMIP6 coupled historical and future simulations. Taking advantage of these developments, we simulated the retreat and regrowth of the Greenland ice sheet during the Last Interglacial period from 127 to 119 thousand years ago – the first fully coupled, full-complexity global Earth system model and higher-order ice sheet model to successfully do so. The simulated evolution of the Greenland ice sheet is consistent with ice core and marine records for this time period. Our CESM2-CISM results suggest that the Greenland ice sheet contributed 4.2-meter sea level equivalent, with rates of sea level rise as high as one millimeter per year for several thousand years. The standalone Greenland ice sheet modeling indicates that there was melting across the whole ice sheet during the peak Last Interglacial warmth, with the central dome of the Greenland ice sheet shifted northward at this time, feeding both NEEM and the Summit ice cores. Glacial inception at the end of the Last Interglacial was also successfully simulated by CESM2-CISM2 – the results establishing a mechanistic link between glacial inception in North America and Scandinavia. The stability of the Greenland ice sheet under anthropogenic warming and its potential contribution to sea level rise over coming centuries and millennia is of vital societal importance. Past warm climate states are ideal proving grounds for models that are to be used for sea level projections. Thus, from a policy perspective, realistic simulation of previous warm periods lends confidence to assessments of future changes. The climate and Greenland ice sheet simulations of the Last Interglacial period benchmarked against paleo observations provides a robust validation of model performance in warm past climate states. To this end, our CESM2-CISM2 simulations of past warm states provide critical confirmation of CESM2-CISM2 and its use for assessing future ice-sheet/climate evolution and sea level rise.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».