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Dataset

 

Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for FAQ 3.2, Figure 1 (v20220615)

Update Frequency: Not Planned
Latest Data Update: 2022-06-17
Status: Completed
Online Status: ONLINE
Publication State: Citable
Publication Date: 2022-06-24
DOI Publication Date: 2023-07-03
Download Stats: last 12 months
Dataset Size: 5 Files | 110KB

Abstract

Data for FAQ 3.2, Figure 1 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).

FAQ 3.2, Figure 1 shows annual, decadal and multi-decadal variations in average global surface temperature. 

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How to cite this dataset
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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:
Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. 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. 423–552, doi:10.1017/9781009157896.005.

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Figure subpanels
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The figure technically has three panels, but they are not labelled. So the datasets are stored just in the main figure folder. 

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List of data provided
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Dataset contains modelled GSAT anomalies from MPI-ESM grand ensemble (1950-2019):

- On annual scale
- On decadal scale
- On multi-decadal scale

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Data provided in relation to figure
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- annual_gsat_anomalies_mpi_esm_grand_ens.csv has data for the left panel, GSAT anomalies from 1950 to 2019 from MPI-ESM grand ensemble (black, light green, light marsh green, light dark green lines)
- decadal_gsat_anomalies_mpi_esm_grand_ens.csv  has data for the middle panel, GSAT anomalies from 1950 to 2019 from MPI-ESM grand ensemble  (black, light green, light marsh green, light dark green lines)
- multi_decadal_gsat_anomalies_mpi_esm_grand_ens.csv has data for the right panel, GSAT anomalies from 1950 to 2019 from MPI-ESM grand ensemble  (black, light green, light marsh green, light dark green lines)

GSAT stands for Global Surface Air Temperature.
MPI-ESM is a comprehensive Earth-System Model, consisting of component models for the ocean, the atmosphere and the land surface.

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Sources of additional information
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The following weblinks are provided in the Related Documents section of this catalogue record:
- Link to the report component containing the figure (Chapter 3)
- Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1
- Link to the figure on the IPCC AR6 website
- Link to the GitHub repo with code for the figure

Citable as:  McGregor, S.; Malinina, E. (2023): Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for FAQ 3.2, Figure 1 (v20220615). NERC EDS Centre for Environmental Data Analysis, 03 July 2023. doi:10.5285/f148031d13954c85b873900cd3f47170. https://dx.doi.org/10.5285/f148031d13954c85b873900cd3f47170
Abbreviation: Not defined
Keywords: IPCC-DDC, IPCC, AR6, WG1, WGI, Sixth Assessment Report, Working Group 1, Physical Science Basis, Annual variations, decadal variations, multi-decadal variations, GSAT, natural variability, global surface air temperature

Details

Previous Info:
No news update for this record
Previously used record identifiers:
No related previous identifiers.
Access rules:
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence: http://creativecommons.org/licenses/by/4.0/. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data lineage:

Data produced by Intergovernmental Panel on Climate Change (IPCC) authors and supplied for archiving at the Centre for Environmental Data Analysis (CEDA) by the Technical Support Unit (TSU) for IPCC Working Group I (WGI).
Data curated on behalf of the IPCC Data Distribution Centre (IPCC-DDC).

Data Quality:
Data as provided by the IPCC
File Format:
Data are netCDF formatted

Process overview

This dataset was generated by the computation detailed below.
Title

Caption for FAQ 3.2, Figure 1 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6)

Abstract

Annual (left), decadal (middle) and multi-decadal (right) variations in average global surface temperature. The thick black line is an estimate of the human contribution to temperature changes, based on climate models, whereas the green lines show the combined effect of natural variations and human-induced warming, different shadings of green represent different simulations, which can be viewed as showing a range of potential pasts. The influence of natural variability is shown by the green bars, and it decreases with longer time scales. The data is sourced from the CESM1 large ensemble.

Input Description

None

Output Description

None

Software Reference

None

  • long_name: Year
  • units: Year
  • var_id: 1
  • units: Degrees C
  • var_id: 2
  • long_name: gsta_black_line_historical_rcp85_r001i1850p3
  • units: Degrees C
  • var_id: 5
  • long_name: gsta_light_dark_green_line_historical_rcp85_r012i1850p3
  • units: Degrees C
  • var_id: 3
  • long_name: gsta_light_green_line_historical_rcp85_r001i1850p3
  • units: Degrees C
  • var_id: 4
  • long_name: gsta_light_marsh_green_line_historical_rcp85_r003i1850p3

Co-ordinate Variables

Coverage
Temporal Range
Start time:
1950-01-01T12:00:00
End time:
2019-12-31T12:00:00
Geographic Extent

 
90.0000°
 
-180.0000°
 
180.0000°
 
-90.0000°