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Enregistrement W6929840282 · doi:10.5063/aa/dpennington.154.1

IPCC Climate Change Data: CGCM1 A2a Model: 2050 Mean Temperature

2005· dataset· en· W6929840282 sur OpenAlexaboutno aff

Notice bibliographique

RevueUC Santa Barbara · 2005
Typedataset
Langueen
DomaineMedicine
ThématiqueChronic Myeloid Leukemia Treatments
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésForcing (mathematics)Climate modelAlbedo (alchemy)Climate changeRadiative forcingAtmospheric modelAtmosphere (unit)Greenhouse gas

Résumé

récupéré en direct d'OpenAlex

The first version of the Canadian Global Coupled Model, CGCM1, and its control climate are described by Flato et al. (1999). The atmospheric component of the model is essentially GCMII described by McFarlane et al. (1992). It is a spectral model with triangular truncation at wave number 32 (yielding a surface grid resolution of roughly 3.7 degrees x3.7 degrees) and 10 vertical levels. The ocean component is based on the GFDL MOM1.1 code and has a resolution of approximately 1.8 degrees x1.8 degrees and 29 vertical levels. The model uses heat and water flux adjustments obtained from uncoupled ocean and atmosphere model runs (of 10 years and 4000 years duration respectively), followed by an `adaption' procedure in which the flux adjustment fields are modified by a 14 year integration of the coupled model. A multi-century control simulation with the coupled model has been performed using the present-day CO2 concentration to evaluate the stability of the coupled model's climate, and to compare the modelled climate and its variability to that observed. An ensemble of four transient climate change simulations has been performed and is described in Boer et al. (1999a; b). Three of these simulations use an effective greenhouse gas forcing change corresponding to that observed from 1850 to the present, and a forcing change corresponding to an increase of CO2 at a rate of 1% per year (compounded) thereafter until year 2100. The direct forcing effect of sulphate aerosols is also included by increasing the surface albedo (as in Reader and Boer, 1999) based on loadings from the sulphur cycle model of Langner and Rodhe (1991). The fourth simulation considers the effect of greenhouse gas forcing only. The change in climate predicted by a model clearly depends directly on this specification of greenhouse gas (and aerosol) forcing, and of course these are not well known. The prescription described above is similar to the IPCC "business as usual" scenario, and using a standard scenario allows the results of this model to be compared to those of other modelling groups around the world. Some initial results from these simulations are presented below. The climate sensitivity of CGCM1 is about 3.5 degrees C. For the A2 emissions scenario the main emphasis is on a strengthening of regional and local culture, with a return to family values in many regions. The A2 world consolidates into a series of roughly continental economic regions, emphasizing local cultural roots. In some regions, increased religious participation leads many to reject a materialist path and to focus attention on contributing to the local community. Elsewhere, the trend is towards ncreased investment in education and science and growth in economic productivity. Social and political structures diversify with some regions moving towards stronger welfare systems and reduced income inequality, while others move towards "lean" government. Environmental concerns are relatively weak, although some attention is paid to bringing local pollution under control and maintaining local environmental amenities. The A2 world sees more international tensions and less cooperation than in A1 or B1. People, ideas and capital are less mobile so that technology diffuses slowly. International disparities in productivity, and hence income per capita, are maintained or increased. With the emphasis on family and community life, fertility rates decline only slowly, although they vary among regions. Hence, this scenario family has high population growth (to 15 billion by 2100) with comparatively low incomes per capita relative to the A1 andB1 worlds, at US$7,200 in 2050 and US$16,000 in 2100.Technological change is rapid in some regions and slow in others as industry adjusts to local resource endowments, culture, and education levels. Regions with abundant energy and mineral resources evolve more resource intensive economies, while those poor in resources place very high priority on minimizing import dependence through technological innovation to improve resource efficiency and make use of substitute inputs. The fuel mix in different regions is determined primarily by resource availability. And divisions among regions persist in terms of their mix of technologies, with high-income but resource-poor regions shifting toward advanced post fossil technologies (renewables in regions of large land availability, nuclear in densely populated, resource poor regions) and low-income resource-rich regions generally relying on older fossil technologies.With substantial food requirements, agricultural productivity is one of the main focus areas for innovation and RD efforts in this future. Initially high levels of soil erosion and water pollution are eventually eased through the local development of more sustainable high-yield agriculture.Although attention is given to potential local and regional environmental damage, it is not uniform across regions. For example, sulfur and particulate emissions are reduced in Asia due to impacts on human health and agricultural production but increase in Africa as a result of the intensified exploitation of coal and other mineral resources. The A2 world sees high energy and carbon intensity, and correspondingly high GHG emissions. Its CO2 emissions are the highest of all four scenario families. Data are available for the following periods: 1961-1990, 2010-2039; 2040-2069; and 2090-2099, mean and monthly change fields.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,025
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0020,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0040,005

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.

Tête enseignante Opus0,058
Tête enseignante GPT0,329
Écart entre enseignants0,271 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreJeu de données

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2005
Routes d'admission1
Résumé présentoui

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