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Enregistrement W6931586659 · doi:10.5285/d32090ff8fe342788191683eb4416411

Chapter 7 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 7.4 (v20230517)

2023· dataset· en· W6931586659 sur OpenAlexaboutno aff

Notice bibliographique

RevueNERC Environmental Data Service · 2023
Typedataset
Langueen
Domaine
Thématique
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésClimate changeRadiative transferClimate modelAtmosphere (unit)CitationTroposphere

Résumé

récupéré en direct d'OpenAlex

Input Data for Figure 7.4 from Chapter 7 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 7.4 shows radiative adjustments at top of atmosphere for seven different climate drivers as a proportion of forcing. --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: Forster, P., T. Storelvmo, K. Armour, W. Collins, J.-L. Dufresne, D. Frame, D.J. Lunt, T. Mauritsen, M.D. Palmer, M. Watanabe, M. Wild, and H. Zhang, 2021: The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 923–1054, doi:10.1017/9781009157896.009. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has 1 panel, with input data provided. A link to the code to plot the figure archived on Zenodo is provided in the Related Documents section of this catalogue record. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains: - Radiative adjustment for tropospheric temperature (orange) - Radiative adjustment for stratospheric temperature (yellow) - Radiative adjustment for water vapour (blue) - Radiative adjustment for surface albedo (green) - Radiative adjustment for clouds (grey) - Total adjustment (black) For the greenhouse gases (carbon dioxide, methane, nitrous oxide and CFC-12) the adjustments are expressed as a percentage of stratospheric-temperature-adjusted radiative forcing (SARF), whereas for aerosol, solar and volcanic forcing they are expressed as a percentage of instantaneous radiative forcing (IRF). Land surface temperature response (outline red bar) is shown, but included in the definition of forcing. Data from Smith et al. (2018b) for carbon dioxide and methane; Smith et al. (2018b) and Gray et al. (2009) for solar; Hodnebrog et al. (2020b) for nitrous oxide and CFC-12; Smith et al. (2020b) for aerosol, and Marshall et al. (2020) for volcanic. IRFs come from offline calculations by Chris and Gunnar (for CAM4) tas_SW, ta_trop_SW, ta_strat_SW. alb_LW are always set to zero. Variables are included in netcdf anyways for consistency. When LW or SW IRFs is not available, The value is set to NaN in the netcdf. When the IRFs are NaN, the corresponding cloud adjustments are also set to NaN. Further details on data sources and processing are available in the chapter data table (Table 7.SM.14). CanESM2 is the Canadian Earth System Model version 2. ECHAM-HAM is the atmospheric General Circulation Model (GCM) from the MPI (Max Planck Institute for Meteorology) - Hamburg Aerosol Model. GISS-E2-R is the Goddard Institute for Space Studies coupled general circulation model (CGCM) - ocean configuration coupled to the Russell OGCM. HadGEM2 is the Met Offfice Hadley Centre Global Environment Model version 2. HadGEM3 is the Met Offfice Hadley Centre Global Environment Model version 3. IPSL-CM5A is the Institut Pierre-Simon Laplace Climate Model for CMIP5. MIROC-SPRINTARS is the Model for Interdisciplinary Research on Climate - Spectral Radiation-Transport Model for Aerosol Species. MPI-ESM is the Max Planck Institute Earth System Model. NCAR-CESM1-CAM4 is the National Center for Atmospheric Research - Community Earth System Model version 1 - Community Atmosphere Model version 4. NCAR-CESM1-CAM5 is the National Center for Atmospheric Research - Community Earth System Model version 1 - Community Atmosphere Model version 5. HadGEM2 is the Met Offfice Hadley Centre Global Environment Model version 2. GFDL is the Geophysical Fluid Dynamics Laboratory. BMRC is the Australian Bureau of Meteorology Research Centre. CCSM4 is the Community Climate System Model version 4. CESM is the Community Earth System Model. ERF stands for Effective Radiative Forcing. IRF stands for Instantaneous Radiative Forcing. TAS stands for Temperature at Surface. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- The CSV file used to plot Figure 7.4 is provided: - 'fig7.4.csv' The github repository contains all input files to the plotting script for the figure except 'rcmip-concentrations-annual-means-v5-1-0.csv'. These are processed and combined in the code to create a single file 'fig7.4.csv' which is provided. The figure can be reproduced using just this file by running the notebook from box 22 by reading in the csv as variable 'adjustments_df'. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- Data and figures are produced by the Jupyter Notebooks that live inside the notebooks directory of the Chapter 7 GitHub repository linked in the Related Documents section. The github repository contains all input files to the notebook except 'rcmip-concentrations-annual-means-v5-1-0.csv'. These are processed and combined in the code to create a single file 'fig7.4.csv' which is provided. The figure can be reproduced using just this file by running the notebook from box 22 by reading in the csv as variable 'adjustments_df'. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the figure on the IPCC AR6 website - Link to the report component containing the figure (Chapter 7) - Link to the Supplementary Material for Chapter 7, which contains details on the input data used in Table 7.SM.1 to 7.SM.7. - Link to the code for the figure, archived on Zenodo. - Link to the notebook for plotting the figure from the Chapter 7 GitHub repository which also contains input data files

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)0,004
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Science ouverte, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesScience ouverte
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 enseignants0,019
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,001
Science ouverte0,0140,026
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,004

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 Opus0,069
Tête enseignante GPT0,319
Écart entre enseignants0,250 · 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
Publié2023
Routes d'admission1
Résumé présentoui

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