A long term study of polar ozone loss derived from data assimilation of Odin/SMR observations
Notice bibliographique
Résumé
Abstract. Odin, a Swedish-led satellite project in collaboration with Canada, France and Finland, was launched on 20 February 2001 and continues to produce profiles of chemical species relevant to understanding the middle and upper atmosphere. Long-term observations of stratospheric ozone are useful for trend analysis of chemical ozone loss. This study concerns ozone loss over both poles utilizing 12 years of ozone data from Odin/Sub-Millimetre Radiometer (SMR). We have applied the data assimilation technique described by Rösevall et al. (2007) with a number of improvements to study the inter-annual variability during the entire Odin period. The chemical ozone losses at potential temperature levels between 425 K and 950 K, (corresponding to an altitude range of 15 to 40 km approximately 90 hPa and 7 hPa in pressure), are derived. Two SMR ozone products retrieved from the emission lines centred at 501 GHz and 544 GHz were used. An internal comparison of the two analyses using 501 GHz and 544 GHz ozone has been carried out by inspecting the vortex mean ozone in March and October during 2002–2013 and 2003–2012 in the Northern and Southern Hemisphere, respectively. Ozone derived from data assimilation using the two data sets match within 10 % at the levels studied, while below 550 K in the Southern Hemispheremore than 50 % of the difference is found. Here, 544 GHz ozone is 0.5 parts per million volume (ppmv) lower than 501 GHz ozone because of better sensitivity in 544 GHz ozone in the lower stratosphere. Comparisons with other studies have been mainly performed against Sonkaew et al. (2013) since Sonkaew et al. (2013) is one of the few studies having consistent estimations of ozone depletion using a SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) from 2002 to 2009. 544 GHz ozone loss in the Arctic winter 2004/2005 is in good agreement with SCIAMACHY loss below 450 K to within 0.2 ppmv, while showing no loss around 550 K where SCIAMACHY detected 0.5 ppmv loss. The comparison of Antarctic ozone depletions with Kuttippurath et al. (2015) shows agreement with MLS ozone loss within 0.1 ppmv, while our results were constantly 0.3 ppmv lower than Mimosa-Chim model calculations. In the Northern Hemisphere, our assimilation analyses show large inter-annual variability. Three classes of chemical ozone losses are found to occur in cold, warm and intermediate winters between cold and warm. The cold type loss maximises in March below 500 K as in the Southern Hemisphere. The maximum loss in the Northern Hemisphere between 2001/2002 and 2012/2013 was during the cold winter, which happened in 2010/2011 with a loss in volume mixing ratio of 2.1 ppmv at 450 K. Losses of 1.5 ppmv took place at 700 K in the warm winters related to the occurrence of mid-winter major sudden stratospheric warming (SSW) events. In the Southern Hemisphere between 2002 and 2012, chemical ozone losses began in mid-August and generally grew to 2.5 ppmv by the end of October. The vertical extent of this loss was 425–550 K. All Antarctic winters except 2002 had approximately 80 DU loss in the stratospheric column. In both hemispheres partial columns in the stratosphere show a small increase over the time period from 2002 to 2013, however the statistical confidence is not high enough to identify ozone recovery.
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 | 0,000 | 0,000 |
| 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) | 0,000 | 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 ».