Dataset
Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.40 (v20220614)
Abstract
Data for Figure 3.40 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).
Figure 3.40 shows the observed and simulated Atlantic Multidecadal Variability (AMV).
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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 has six panels. Files are not separated according to the panels.
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List of data provided
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amv.obs.nc contains
- Observed SST anomalies associated with the AMV pattern
- Observed AMV index time series (unfiltered)
- Observed AMV index time series (low-pass filtered)
- Taylor statistics of the observed AMV patterns
amv.hist.cmip6.nc contains
- Statistical significance of the observed SST anomalies associated with the AMV pattern
- Simulated SST anomalies associated with the AMV pattern
- Simulated AMV index time series (unfiltered)
- Simulated AMV index time series (low-pass filtered)
- Taylor statistics of the simulated AMV patterns
based on CMIP6 historical simulations.
amv.hist.cmip5.nc contains
- Simulated SST anomalies associated with the AMV pattern
- Simulated AMV index time series (unfiltered)
- Simulated AMV index time series (low-pass filtered)
- Taylor statistics of the simulated AMV patterns
based on CMIP5 historical simulations.
amv.piControl.cmip6.nc contains
- Simulated SST anomalies associated with the AMV pattern
- Simulated AMV index time series (unfiltered)
- Simulated AMV index time series (low-pass filtered)
- Taylor statistics of the simulated AMV patterns
based on CMIP6 piControl simulations.
amv.piControl.cmip5.nc contains
- Simulated SST anomalies associated with the AMV pattern
- Simulated AMV index time series (unfiltered)
- Simulated AMV index time series (low-pass filtered)
- Taylor statistics of the simulated AMV patterns
based on CMIP5 piControl simulations.
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Data provided in relation to figure
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Panel a:
- amv_pattern_obs_ref in amv.obs.nc: shading
- amv_pattern_obs_signif (dataset = 1) in amv.obs.nc: cross markers
Panel b:
- Multimodel ensemble mean of amv_pattern in amv.hist.cmip6.nc: shading, with their sign agreement for hatching
Panel c:
- tay_stats (stat = 0, 1) in amv.obs.nc: black dots
- tay_stats (stat = 0, 1) in amv.hist.cmip6.nc: red crosses, and their multimodel ensemble mean for the red dot
- tay_stats (stat = 0, 1) in amv.hist.cmip5.nc: blue crosses, and their multimodel ensemble mean for the blue dot
Panel d:
- Lag-1 autocorrelation of amv_timeseries_raw in amv.obs.nc: black horizontal lines in left
. ERSSTv5: dataset = 1
. HadISST: dataset = 2
. COBE-SST2: dataset = 3
- Multimodel ensemble mean and percentiles of lag-1 autocorrelation of amv_timeseries_raw in amv.piControl.cmip5.nc: blue open box-whisker in the left
- Multimodel ensemble mean and percentiles of lag-1 autocorrelation of amv_timeseries_raw in amv.piControl.cmip6.nc: red open box-whisker in the left
- Multimodel ensemble mean and percentiles of lag-1 autocorrelation of amv_timeseries_raw in amv.hist.cmip5.nc: blue filled box-whisker in the left
- Multimodel ensemble mean and percentiles of lag-1 autocorrelation of amv_timeseries_raw in amv.hist.cmip6.nc: red filled box-whisker in the left
- Lag-10 autocorrelation of amv_timeseries in amv.obs.nc: black horizontal lines in right
. ERSSTv5: dataset = 1
. HadISST: dataset = 2
. COBE-SST2: dataset = 3
- Multimodel ensemble mean and percentiles of lag-10 autocorrelation of amv_timeseries in amv.piControl.cmip5.nc: blue open box-whisker in the right
- Multimodel ensemble mean and percentiles of lag-10 autocorrelation of amv_timeseries in amv.piControl.cmip6.nc: red open box-whisker in the right
- Multimodel ensemble mean and percentiles of lag-10 autocorrelation of amv_timeseries in amv.hist.cmip5.nc: blue filled box-whisker in the right
- Multimodel ensemble mean and percentiles of lag-10 autocorrelation of amv_timeseries in amv.hist.cmip6.nc: red filled box-whisker in the right
Panel e:
- Standard deviation of amv_timeseries_raw in amv.obs.nc: black horizontal lines in left
. ERSSTv5: dataset = 1
. HadISST: dataset = 2
. COBE-SST2: dataset = 3
- Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries_raw in amv.piControl.cmip5.nc: blue open box-whisker in the left
- Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries_raw in amv.piControl.cmip6.nc: red open box-whisker in the left
- Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries_raw in amv.hist.cmip5.nc: blue filled box-whisker in the left
- Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries_raw in amv.hist.cmip6.nc: red filled box-whisker in the left
- Standard deviation of amv_timeseries in amv.obs.nc: black horizontal lines in right
. ERSSTv5: dataset = 1
. HadISST: dataset = 2
. COBE-SST2: dataset = 3
- Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries in amv.piControl.cmip5.nc: blue open box-whisker in the right
- Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries in amv.piControl.cmip6.nc: red open box-whisker in the right
- Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries in amv.hist.cmip5.nc: blue filled box-whisker in the right
- Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries in amv.hist.cmip6.nc: red filled box-whisker in the right
Panel f:
- amv_timeseries in amv.obs.nc: black curves
. ERSSTv5: dataset = 1
. HadISST: dataset = 2
. COBE-SST2: dataset = 3
- amv_timeseries in amv.hist.cmip6.nc: 5th-95th percentiles in red shading, multimodel ensemble mean and its 5-95% confidence interval for red curves
- amv_timeseries in amv.hist.cmip5.nc: 5th-95th percentiles in blue shading, multimodel ensemble mean for blue curve
CMIP5 is the fifth phase of the Coupled Model Intercomparison Project.
CMIP6 is the sixth phase of the Coupled Model Intercomparison Project.
SST stands for Sea Surface Temperature.
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Notes on reproducing the figure from the provided data
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Multimodel ensemble means and percentiles of historical simulations of CMIP5 and CMIP6 are calculated 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.
piControl simulations from CMIP5 and CMIP6 consist of a single member from each model, so the weighting is not applied.
Multimodel ensemble means of the pattern correlation in Taylor statistics in (c) and the autocorrelation of the index in (d) are calculated via Fisher z-transformation and back transformation.
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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 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
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| Previously used record identifiers: |
No related previous identifiers.
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| 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 Quality: |
Data as provided by the IPCC
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| File Format: |
Data are netCDF formatted
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Related Documents
Process overview
| Title | Caption for Figure 3.40 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 Atlantic Multi-decadal Variability (AMV). (a, b) Sea surface temperature (SST) anomalies (ºC) regressed onto the AMV index defined as the 10-year low-pass filtered North Atlantic (0º–60°N, 80°W–0°E) area-weighted SST* anomalies over 1900–2014 in (a) ERSST version 5 and (b) the CMIP6 multi-model ensemble (MME) mean composite obtained by weighting ensemble members by the inverse of each model’s ensemble size. The asterisk denotes that the global mean SST anomaly has been removed at each time step of the computation. Cross marks in (a) represent regions where the anomalies are not significant at the 10% level based on a t-test. Diagonal lines in (b) show regions where less than 80% of the runs agree in sign. (c) A Taylor diagram summarizing the representation of the AMV pattern in CMIP5 (each member is shown as a cross in light blue, and the weighted multi-model mean is shown as a dot in dark blue), CMIP6 (each member is shown as a cross in red, and the weighted multi-model mean is shown as a dot in orange) and observations over [0º–60°N, 80°W–0°E]. The reference pattern is taken from ERSST version 5 and black dots indicate other observational products (HadISST version 1 and COBE-SST2). (d) Autocorrelation of unfiltered annual AMV index at lag one year and 10-year low-pass filtered AMV index at lag 10 years for observations over 1900–2014 (horizontal lines) and 115-year chunks of pre-industrial control simulations (open boxes) and individual historical simulations over 1900–2014 (filled boxes) from CMIP5 (blue) and CMIP6 (red). (e) As in (d), but showing standard deviation of the unfiltered and filtered AMV indices (ºC). Boxes and whiskers show the weighted multi-model mean, interquartile ranges and 5th and 95th percentiles. (f) Time series of the AMV index (ºC) in ERSST version 5, HadISST version 1 and COBE-SST2 observational estimates (black) and CMIP5 and CMIP6 historical simulations. The thick red and light blue lines are the weighted multi-model mean for the historical simulations in CMIP5 and CMIP6, respectively, and the envelopes represent the 5th–95th percentile range obtained from all ensemble members. The 5–95% confidence interval for the CMIP6 multi-model mean is shown by the thin dashed line. 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
- units: K
- standard_name: sea_surface_temperature
- long_name: Sea Surface Temperature
- var_id: amv_pattern_obs_signif
- long_name: Taylor statistics
- var_id: tay_stats
- var_id: amv_pattern
- var_id: dataset
- var_id: dim_cmip5_hist
- var_id: ensemble_assign
- var_id: stat
- units: K
- var_id: amv_timeseries_raw
- long_name: the AMV index
- units: K
- var_id: amv_timeseries
- long_name: the low-pass filtered AMV index
Co-ordinate Variables
- units: degrees_north
- standard_name: latitude
- var_id: lat
- units: degrees_east
- standard_name: longitude
- var_id: lon
- long_name: time
- standard_name: time
- var_id: time
- units: days
Temporal Range
1900-01-01T12:00:00
2014-12-31T12:00:00
Geographic Extent
90.0000° |
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-180.0000° |
180.0000° |
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-90.0000° |