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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 on OpenAlexaboutno aff

Bibliographic record

VenueNERC Environmental Data Service · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeRadiative transferClimate modelAtmosphere (unit)CitationTroposphere

Abstract

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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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
Consensus categoriesOpen science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0140.026
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.069
GPT teacher head0.319
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
Has abstractyes

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