Spatio-temporal variability of Arctic summer temperatures over the past two millennia: an overview of the last major climate anomalies
Notice bibliographique
Résumé
Abstract. In this article, the first spatially resolved millennium-long summer (June–August) temperature reconstruction over the Arctic and Subarctic domain (north of 60° N) is presented. It is based on a set of 54 annually dated temperature sensitive proxy archives of various types, mainly from the updated and revised PAGES2k database supplemented with 6 new recently published proxy records. As a major novelty, an extension of the Bayesian BARCAST climate field (CF) reconstruction technique provides a means to treat climate archives with dating uncertainties. In total 1400 realisations of the temperature CF were generated, enabling further analyses to be carried out in a probabilistic framework. The new seasonal CF reconstruction for the Arctic region can be shown to be skilful for the majority of the terrestrial nodes. The decrease in the proxy data density back in time however limits the analyses in the spatial domain to the period after 750 CE, while the spatially averaged reconstruction covers the entire time interval of 1–2002 CE. The analysis of basic features of the reconstructed seasonal CF focuses on the regional expression of past major climate anomalies in order to uncover the potential of the new product for studying Common Era temperature variability in the region. The long-term, centennial to millennial, evolution of the reconstructed temperature is in good agreement with a general pattern that was inferred in recent studies for the Arctic and its sub-regions. On the pan-Arctic scale the reconstruction shows a cooling trend which is, however, statistically insignificant and the estimated magnitude of the millennial scale cooling is three times smaller than inferred in the previous studies. The trend is spatially heterogeneous and for some regions such as Greenland the reconstruction demonstrates a tendency to the warming instead. The reconstruction shows a pronounced Medieval Climate Anomaly (MCA, here, ca. ~ 960–1060 CE), which was characterised by a sequence of extremely warm decades over the whole domain. The medieval warming was followed by a gradual cooling into the Little Ice Age (LIA), with 1580–1680 CE as the longest centennial-scale cold period, culminating around 1812–1822 CE for most of the target region. At the same time there is evidence for a drastic reduction in sea-ice on the Greenland shelf, which is reflected by rather high summer temperatures over Greenland and Baffin Island during that decade. During the MCA, the contrast between reconstructed summer temperatures over mid- and high-latitudes in Europe and the European/North Atlantic sector of the Arctic shows a very dynamic expression of the Arctic amplification, with leads and lags between continental and more marine and extreme latitude settings. While our analysis shows that the peak MCA summer temperatures were as high as in the late 20th and early 21st century, the spatial coherence of extreme years over the last decades seems unprecedented at least back until 750 CE. However, statistical testing could not provide conclusive support of the contemporary warming to supersede the peak of the MCA in terms of the pan-Arctic mean summer temperatures.
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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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,001 | 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 ».