Dataset
Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.33 (v20211209)
Abstract
Data for Figure 3.33 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).
Figure 3.33 shows observed and simulated Northern Annular Mode (NAM), North Atlantic Oscillation (NAO) and Southern Annular Mode (SAM) in boreal winter.
---------------------------------------------------
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:
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.
---------------------------------------------------
Figure subpanels
---------------------------------------------------
The figure has twelve panels, with data provided for panels (a), (d), (g) and (j) in the subdirectory named panel_adgj, panels (b), (e), (h) and (k) in the subdirectory named panel_behk, and panels (c), (f), (i) and (l) in the subdirectory named panel_cfil.
---------------------------------------------------
List of data provided
---------------------------------------------------
This dataset contains:
- Observed sea level pressure anomalies associated with NAM.
- Observed sea level pressure anomalies associated with NAO.
- Observed sea level pressure anomalies associated with SAM.
- Simulated sea level pressure anomalies associated with NAM.
- Simulated sea level pressure anomalies associated with NAO.
- Simulated sea level pressure anomalies associated with SAM.
- Taylor statistics of sea level pressure anomalies associated with NAM.
- Taylor statistics of sea level pressure anomalies associated with NAO.
- Taylor statistics of sea level pressure anomalies associated with SAM.
- 1958-2014 trends of the NAM index.
- 1958-2014 trends of the NAO index.
- 1979-2014 trends of the SAM index.
---------------------------------------------------
Data provided in relation to figure
---------------------------------------------------
Panel a:
- nam_patterns(0, :, :) in panel_adgj/nam.obs.nc; shading
- nam_pattern_significance in panel_adgj/nam.obs.nc; cross marker
Panel b:
- nao_patterns(0, :, :) in panel_behk/nao.obs.nc; shading
- nao_pattern_significance in panel_behk/nao.obs.nc; cross marker
Panel c:
- sam_patterns(0, :, :) in panel_cfil/sam.obs.nc; shading
- sam_pattern_significance in panel_cfil/sam.obs.nc; cross marker
Panel d:
- nam_patterns in panel_adgj/nam.hist.cmip6.nc; multimodel ensemble mean for shading, and sign agreement for hatching
Panel e:
- nao_patterns in panel_behk/nao.hist.cmip6.nc; multimodel ensemble mean for shading, and sign agreement for hatching
Panel f:
- sam_patterns in panel_cfil/sam.hist.cmip6.nc; multimodel ensemble mean for shading, and sign agreement for hatching
Panel g:
- nam_tay_stat(:, 0:1) in panel_adgj/nam.amip.cmip6.nc: multimodel ensemble mean for the orange dot
- nam_tay_stat(:, 0:1) in panel_adgj/nam.hist.cmip5.nc: blue crosses, with multimodel ensemble mean for the blue dot
- nam_tay_stat(:, 0:1) in panel_adgj/nam.hist.cmip6.nc: red crosses, with multimodel ensemble mean for the red dot
- nam_tay_stat(:, 0:1) in panel_adgj/nam.obs.nc: black dots
Panel h:
- nao_tay_stat(:, 0:1) in panel_behk/nao.amip.cmip6.nc: multimodel ensemble mean for the orange dot
- nao_tay_stat(:, 0:1) in panel_behk/nao.hist.cmip5.nc: blue crosses, with multimodel ensemble mean for the blue dot
- nao_tay_stat(:, 0:1) in panel_behk/nao.hist.cmip6.nc: red crosses, with multimodel ensemble mean for the red dot
- nao_tay_stat(:, 0:1) in panel_behk/nao.obs.nc: black dots
Panel i:
- sam_tay_stat(:, 0:1) in panel_cfil/sam.amip.cmip6.nc: multimodel ensemble mean for the orange dot
- sam_tay_stat(:, 0:1) in panel_cfil/sam.hist.cmip5.nc: blue crosses, with multimodel ensemble mean for the blue dot
- sam_tay_stat(:, 0:1) in panel_cfil/sam.hist.cmip6.nc: red crosses, with multimodel ensemble mean for the red dot
- sam_tay_stat(:, 0:1) in panel_cfil/sam.obs.nc: black dots
Panel j:
- nam_pc_trends in panel_adgj/nam.amip.cmip6.nc: multimodel ensemble mean for orange vertical line
- nam_pc_trends in panel_adgj/nam.hist.cmip5.nc: multimodel ensemble mean for blue vertical line
- nam_pc_trends in panel_adgj/nam.hist.cmip6.nc: histogram, with multimodel ensemble mean for red vertical line
- nam_pc_trends in panel_adgj/nam.obs.nc: black vertical lines
Panel k:
- nao_pc_trends in panel_behk/nao.amip.cmip6.nc: multimodel ensemble mean for orange vertical line
- nao_pc_trends in panel_behk/nao.hist.cmip5.nc: multimodel ensemble mean for blue vertical line
- nao_pc_trends in panel_behk/nao.hist.cmip6.nc: histogram, with multimodel ensemble mean for red vertical line
- nao_pc_trends in panel_behk/nao.obs.nc: black vertical lines
Panel l:
- sam_pc_trends in panel_cfil/sam.amip.cmip6.nc: multimodel ensemble mean for orange vertical line
- sam_pc_trends in panel_cfil/sam.hist.cmip5.nc: multimodel ensemble mean for blue vertical line
- sam_pc_trends in panel_cfil/sam.hist.cmip6.nc: histogram, with multimodel ensemble mean for red vertical line
- sam_pc_trends in panel_cfil/sam.obs.nc: black vertical lines
---------------------------------------------------
Notes on reproducing the figure from the provided data
---------------------------------------------------
Multimodel ensemble means and histograms are obtained after weighting individual members with the inverse of the ensemble size of the same model. ensemble_assign in each file provides the model number to which each ensemble member belongs. This weighting does not apply to the sign agreement calculation.
Multimodel ensemble mean of the pattern correlation in Taylor statistics is calculated via Fisher z-transformation and back transformation.
---------------------------------------------------
Sources of additional information
---------------------------------------------------
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 supporting information on the figure in Section and details on the input data used in Table 3.SM.1
- Link to the code for the figure, archived on Zenodo
- Link to the figure on the IPCC AR6 website
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(s): 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 Quality: |
Data as provided by the IPCC
|
| File Format: |
netCDF
|
Related Documents
Process overview
| Title | Caption for Figure 3.33 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6) |
| Abstract | Model evaluation of NAM, NAO and SAM in boreal winter. Regression of Mean Sea Level Pressure (MSLP) anomalies (in hPa) onto the normalized principal component (PC) of the leading mode of variability obtained from empirical orthogonal decomposition of the boreal winter (December–February) MSLP poleward of 20ºN for the observed Northern Annular Mode (NAM, a), over 20ºN–80°N, 90°W–40°E for the North Atlantic Oscillation as shown by the black sector (NAO, b), and poleward of 20ºS for the Southern Annular Mode (SAM, c) for the JRA-55 reanalysis. Cross marks indicate regions where the anomalies are not significant at the 10% level based on t-test. The period used to calculate the NAO/NAM is 1958–2014 but 1979–2014 for the SAM. (d–f) Same but for the multi-model ensemble (MME) mean from CMIP6 historical simulations. Models are weighted in compositing to account for differences in their respective ensemble size. Diagonal lines stand for regions where less than 80% of the runs agree in sign. (g–i) Taylor diagram summarizing the representation of the modes in models and observations following Lee et al. (2019) for CMIP5 (light blue) and CMIP6 (red) historical runs. The reference pattern is taken from JRA-55 (a–c). The ratio of standard deviation (radial distance), spatial correlation (radial angle) and resulting root-mean-squared errors (solid isolines) are given for individual ensemble members (crosses) and for other observational products (ERA5 and NOAA 20CR version 3, black dots). Coloured dots stand for weighted multi-model mean statistics for CMIP5 (blue) and CMIP6 (light red) as well as for AMIP simulations from CMIP6 (orange). (j–l) Histograms of the trends built from all individual ensemble members and all the models (brown bars). Vertical lines in black show all the observational estimates. The orange, light red, and light blue lines indicate the weighted multi-model mean of CMIP6 AMIP, CMIP6 and CMIP5 historical simulations, respectively. Further details on data sources and processing are available in the chapter data table (Table 3.SM.1). |
| Input Description | None |
| Output Description | None |
| Software Reference | None |
- var_id: E
- long_name: Taylor statistics
- var_id: sam_tay_stat
- names: Taylor statistics
- var_id: dataset
- var_id: ensemble_assign
- var_id: nam_pattern_significance
- units: Pa
- var_id: nam_patterns
- units: (56 years)^-1
- var_id: nam_pc_trends
- var_id: nao_pattern_significance
- units: Pa
- var_id: nao_patterns
- units: (56 years)^-1
- var_id: nao_pc_trends
- var_id: sam_pattern_significance
- units: Pa
- var_id: sam_patterns
- units: (36 years)^-1
- var_id: sam_pc_trends
- var_id: stat
Co-ordinate Variables
- units: degrees_north
- standard_name: latitude
- long_name: latitude
- var_id: lat
- names: latitude
- units: degrees_east
- standard_name: longitude
- long_name: longitude
- var_id: lon
- names: longitude
Temporal Range
1959-01-01T12:00:00
2014-12-31T12:00:00
Geographic Extent
90.0000° |
||
-180.0000° |
180.0000° |
|
-90.0000° |