Assessing the role of atmospheric rivers in Arctic precipitation and temperature in present and future climate
Notice bibliographique
Résumé
In recent decades, the Arctic has experienced remarkable changes, including enhanced poleward heat and moisture transport. Atmospheric rivers (ARs), defined as long and narrow corridors with high moisture content, are renowned for their significant moisture transport, with implications on temperature and precipitation. Along with the faster warming, precipitation phase (snow vs. rain) plays a major role in the Arctic, as rainfall contributes to sea-ice decline, thereby triggering the ice-albedo feedback. Since previous studies indicate increasing moisture transport towards the Polar Regions, it is crucial to understand the changes in ARs reaching the Arctic in present and future climates and their impacts in a warmer climate. This thesis started by adapting an algorithm used for AR identification, applied to specific case studies. Building on this knowledge, the study was extended to cover the last 43 years, including further improvement of the algorithm, evaluation of the data used, assessment of changes in the AR characteristics, and the analysis of their impacts, with a specific emphasis on precipitation, its phase, and temperature. The final step involved studying ARs in a future climate under various scenarios. After evaluating the available models, the algorithm was applied, followed by the study of AR changes and their impacts in a future climate. This thesis relied on observational and reanalysis datasets, and model simulations. The detailed analysis of the case studies focused on the synoptic-scale evolution, thermodynamic, and precipitation properties during three intense AR events reaching Svalbard in May-June 2017 during the ACLOUD/PASCAL campaign. The results underscore the importance of using data with adequate temporal and spatial resolution and the relevance of employing different AR detection algorithms. After, this study was extended from 1980 to 2022 and the results show a poleward shift of AR frequency and their intensification in the North Atlantic pathway. ARs are responsible for over 20% of precipitation in the Atlantic, concurrently with AR-related snowfall on coastal Greenland and AR-related rainfall in the open ocean. Recent trends show increasing AR-related rainfall and decreasing AR-related snowfall, concurrently with positive temperature trends and increasing AR moisture content. After the comparison of different algorithms, the necessity of using various methods became more evident. Finally, the future AR climatology was analysed using MRI-ESM2.0 CMIP6 model under SSP1-2.6 and SSP5-8.5 (2081-2100), in comparison with results from 1995 to 2014. Results project higher AR frequency and intensity, along with a poleward shift in the North Atlantic pathway and an increasing significance of the Pacific and Canadian Arctic. Finally, in the future AR-related rainfall and temperature are expected to increase, conversely to a decrease in AR-related snowfall. These changes are amplified in the SSP5-8.5 scenario.
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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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».