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Dataset

 

Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.37 (v20220620)

Update Frequency: Not Planned
Latest Data Update: 2022-06-20
Status: Completed
Online Status: ONLINE
Publication State: Citable
Publication Date: 2022-06-27
DOI Publication Date: 2023-02-08
Download Stats: last 12 months
Dataset Size: 3 Files | 53KB
Abstract

Data for Figure 3.37 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).

Figure 3.37 shows observed and simulated seasonality of ENSO.

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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 two panels. All the data are provided in enso_seasonality.nc.

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List of data provided
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This dataset contains

- Climatological standard deviation of the ENSO index
- A seasonality metric of the ENSO index

in observations, CMIP5 historical-RCP4.5 and CMIP6 historical simulations.

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Data provided in relation to figure
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Panel a:
- stdv_enso_obs; black curves
. ERSSTv5, dashed lines: dataset = 1
. HadISST, solid lines: dataset = 2
- stdv_enso_cmip5: Climatological standard deviation of the ENSO index time series in each ensemble member of CMIP5 models blue curve and shading
- stdv_enso_cmip6: Climatological standard deviation of the ENSO index time series in each ensemble member of CMIP6 models; red curve and shading
. ACCESS-CM2: ens_cmip6 = 1 - 3
. ACCESS-ESM1-5: ens_cmip6 = 4 - 23
. AWI-CM-1-1-MR: ens_cmip6 = 24 - 28
. AWI-ESM-1-1-LR: ens_cmip6 = 29
. BCC-CSM2-MR: ens_cmip6 = 30 - 32
. BCC-ESM1: ens_cmip6 = 33 - 35
. CAMS-CSM1-0: ens_cmip6 = 36-38
. CanESM5-CanOE: ens_cmip6 = 39 - 41
. CanESM5: ens_cmip6 = 42 - 106
. CESM2-FV2: ens_cmip6 = 107 - 109
. CESM2: ens_cmip6 = 110 - 120
. CESM2-WACCM-FV2: ens_cmip6 = 121 - 123
. CESM2-WACCM: ens_cmip6 = 124 - 126
. CIESM: ens_cmip6 = 127 - 129
. CMCC-CM2-HR4: ens_cmip6 = 130
. CMCC-CM2-SR5: ens_cmip6 = 131
. CMCC-ESM2: ens_cmip6 = 132
. CNRM-CM6-1-HR: ens_cmip6 = 133
. CNRM-CM6-1: ens_cmip6 = 134 - 162
. CNRM-ESM2-1: ens_cmip6 = 163 - 172
. E3SM-1-0: ens_cmip6 = 173 - 177
. E3SM-1-1-ECA: ens_cmip6 = 178
. E3SM-1-1: ens_cmip6 = 179
. EC-Earth3-AerChem: ens_cmip6 = 180, 181
. EC-Earth3-CC: ens_cmip6 = 182
. EC-Earth3: ens_cmip6 = 183 - 204
. EC-Earth3-Veg-LR: ens_cmip6 = 205 - 207
. EC-Earth3-Veg: ens_cmip6 = 208 - 215
. FGOALS-f3-L: ens_cmip6 = 216 - 218
. FGOALS-g3: ens_cmip6 = 219 - 224
. FIO-ESM-2-0: ens_cmip6 = 225 - 227
. GFDL-CM4: ens_cmip6 = 228
. GFDL-ESM4: ens_cmip6 = 229 - 231
. GISS-E2-1-G-CC: ens_cmip6 = 232
. GISS-E2-1-G: ens_cmip6 = 233 - 278
. GISS-E2-1-H: ens_cmip6 = 279 - 302
. HadGEM3-GC31-LL: ens_cmip6 = 303 - 306
. HadGEM3-GC31-MM: ens_cmip6 = 307 - 310
. IITM-ESM: ens_cmip6 = 311
. INM-CM4-8: ens_cmip6 = 312
. INM-CM5-0: ens_cmip6 = 313 - 322
. IPSL-CM5A2-INCA: ens_cmip6 = 323
. IPSL-CM6A-LR: ens_cmip6 = 324 - 355
. KACE-1-0-G: ens_cmip6 = 356-358
. KIOST-ESM: ens_cmip6 = 359
. MCM-UA-1-0: ens_cmip6 = 360, 361
. MIROC6: ens_cmip6 = 362 - 411
. MIROC-ES2L: ens_cmip6 = 412 - 421
. MPI-ESM-1-2-HAM: ens_cmip6 = 422 - 424
. MPI-ESM1-2-HR: ens_cmip6 = 425 - 434
. MPI-ESM1-2-LR: ens_cmip6 = 435 -  444
. MRI-ESM2-0: ens_cmip6 = 445 - 450
. NESM3: ens_cmip6 = 451 - 455
. NorCPM1: ens_cmip6 = 456 - 485
. NorESM2-LM: ens_cmip6 = 486 - 488
. NorESM2-MM: ens_cmip6 = 489 - 490
. SAM0-UNICON: ens_cmip6 = 491
. TaiESM1: ens_cmip6 = 492
. UKESM1-0-LL: ens_cmip6 = 493 - 510

Panel b:
- seasonality_enso_obs; black vertical lines and numbers in the top right box
. ERSSTv5, dashed lines: dataset = 1
. HadISST, solid lines: dataset = 2
- seasonality_enso_cmip5; Seasonality metric in each ensemble member of CMIP5 models; blue box-whisker and number in the top right box
- seasonality_enso_cmip6; Seasonality metric in each ensemble member of CMIP6 models; red dots, with their multimodal ensemble mean and percentiles for the red box-whisker and number in the top right box
. ACCESS-CM2: ens_cmip6 = 1 - 3
. ACCESS-ESM1-5: ens_cmip6 = 4 - 23
. AWI-CM-1-1-MR: ens_cmip6 = 24 - 28
. AWI-ESM-1-1-LR: ens_cmip6 = 29
. BCC-CSM2-MR: ens_cmip6 = 30 - 32
. BCC-ESM1: ens_cmip6 = 33 - 35
. CAMS-CSM1-0: ens_cmip6 = 36-38
. CanESM5-CanOE: ens_cmip6 = 39 - 41
. CanESM5: ens_cmip6 = 42 - 106
. CESM2-FV2: ens_cmip6 = 107 - 109
. CESM2: ens_cmip6 = 110 - 120
. CESM2-WACCM-FV2: ens_cmip6 = 121 - 123
. CESM2-WACCM: ens_cmip6 = 124 - 126
. CIESM: ens_cmip6 = 127 - 129
. CMCC-CM2-HR4: ens_cmip6 = 130
. CMCC-CM2-SR5: ens_cmip6 = 131
. CMCC-ESM2: ens_cmip6 = 132
. CNRM-CM6-1-HR: ens_cmip6 = 133
. CNRM-CM6-1: ens_cmip6 = 134 - 162
. CNRM-ESM2-1: ens_cmip6 = 163 - 172
. E3SM-1-0: ens_cmip6 = 173 - 177
. E3SM-1-1-ECA: ens_cmip6 = 178
. E3SM-1-1: ens_cmip6 = 179
. EC-Earth3-AerChem: ens_cmip6 = 180, 181
. EC-Earth3-CC: ens_cmip6 = 182
. EC-Earth3: ens_cmip6 = 183 - 204
. EC-Earth3-Veg-LR: ens_cmip6 = 205 - 207
. EC-Earth3-Veg: ens_cmip6 = 208 - 215
. FGOALS-f3-L: ens_cmip6 = 216 - 218
. FGOALS-g3: ens_cmip6 = 219 - 224
. FIO-ESM-2-0: ens_cmip6 = 225 - 227
. GFDL-CM4: ens_cmip6 = 228
. GFDL-ESM4: ens_cmip6 = 229 - 231
. GISS-E2-1-G-CC: ens_cmip6 = 232
. GISS-E2-1-G: ens_cmip6 = 233 - 278
. GISS-E2-1-H: ens_cmip6 = 279 - 302
. HadGEM3-GC31-LL: ens_cmip6 = 303 - 306
. HadGEM3-GC31-MM: ens_cmip6 = 307 - 310
. IITM-ESM: ens_cmip6 = 311
. INM-CM4-8: ens_cmip6 = 312
. INM-CM5-0: ens_cmip6 = 313 - 322
. IPSL-CM5A2-INCA: ens_cmip6 = 323
. IPSL-CM6A-LR: ens_cmip6 = 324 - 355
. KACE-1-0-G: ens_cmip6 = 356-358
. KIOST-ESM: ens_cmip6 = 359
. MCM-UA-1-0: ens_cmip6 = 360, 361
. MIROC6: ens_cmip6 = 362 - 411
. MIROC-ES2L: ens_cmip6 = 412 - 421
. MPI-ESM-1-2-HAM: ens_cmip6 = 422 - 424
. MPI-ESM1-2-HR: ens_cmip6 = 425 - 434
. MPI-ESM1-2-LR: ens_cmip6 = 435 -  444
. MRI-ESM2-0: ens_cmip6 = 445 - 450
. NESM3: ens_cmip6 = 451 - 455
. NorCPM1: ens_cmip6 = 456 - 485
. NorESM2-LM: ens_cmip6 = 486 - 488
. NorESM2-MM: ens_cmip6 = 489 - 490
. SAM0-UNICON: ens_cmip6 = 491
. TaiESM1: ens_cmip6 = 492
. UKESM1-0-LL: ens_cmip6 = 493 - 510

Acronyms - ENSO - El Niño–Southern Oscillation, CMIP - Coupled Model Intercomparison Project, RCP - Representative Concentration Pathway, ERSST - Extended Reconstructed Sea Surface Temperature, HadISST - Hadley Centre Sea Ice and Sea Surface Temperature, ACCESS- CM2 – Australian Community Climate and Earth System Simulator coupled climate model, ACCESS- ESM – Australian Community Climate and Earth System Simulator Earth system model, AWI - Alfred Wegener Institute, BCC-CSM - Beijing Climate Center Climate System Model, CAMS - Chinese Academy of Meteorological Sciences, CanOE - Canadian Ocean Ecosystem, CESM2 - Community Earth System Model, WACCM - Whole Atmosphere Community Climate Model, CIESM - Community Integrated Earth System Model, CNCC - Centro Euro-Mediterraneo per I Cambiamenti Climatici, CNRM - Centre National de Recherches Météorologiques, E3SM - Energy Exascale Earth System Model, FGOALS - Flexible Global Ocean-Atmosphere-Land System Model, FIO-ESM - First Institute of Oceanography Earth System Model, GFDL - Geophysical Fluid Dynamics Laboratory, GISS - Goddard Institute for Space Studies, IITM - Indian Institute of Tropical Meteorology, INM - Institute for Numerical Mathematics, IPSL - Institut Pierre-Simon Laplace, KIOST-ESM - Korea Institute of Ocean Science & Technology Earth System, MIROC - Model for Interdisciplinary Research on Climate, MPI - Max-Planck-Institut für Meteorologie, NESM - Nanjing University of Information Science and Technology Earth System Model, NorCPM - Norwegian Climate Prediction Model, SAM0-UNICON - Seoul National University Atmosphere Model version 0 with a Unified Convection Scheme (SAM0-UNICON), TaiESM1 - Taiwan Earth System Model version 1, UKESM - The UK Earth System Modelling project.

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Notes on reproducing the figure from the provided data
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Multimodel ensemble means and percentiles are calculated after weighting individual members with the inverse of the ensemble size of the same model. The weight is provided as the weight attribute of ens_cmip5 and ens_cmip6.

If X(i) is the array, and w(i) the corresponding weight.

- Mean shoud be suｍ_i(X(i) * w(i)) / sum_i(w(i))

- For percentile values,

1. Sort X and w so that X is in the ascending order

2. Accumulate w until i = j so that accumulated(w)/sum_i(w(i)) equals or exceeds the specified percentile level (e.g. 0.05)

3. Use X(j) or (X(j) + X(j - 1))/2 as the percentile value

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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

Citable as:  Kosaka, Y.; McGregor, S.; Cassou, C.; Kazeroni, R. (2023): Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.37 (v20220620). NERC EDS Centre for Environmental Data Analysis, 08 February 2023. doi:10.5285/babcd0de678e4d10aef395f1a265da03. https://dx.doi.org/10.5285/babcd0de678e4d10aef395f1a265da03
Abbreviation: Not defined
Keywords: IPCC-DDC, IPCC, AR6, WG1, WGI, Sixth Assessment Report, Working Group 1, Physical Science Basis, ENSO, modes of variability, seasonality, CMIP5, CMIP6

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

Related Documents

 CODE FOR FIGURE (archived at Zenodo)
 ORIGIN OF FIGURE (IPCC REPORT CHAPTER): 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
 SUPPLEMENTARY MATERIAL FOR REPORT CHAPTER: 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 Supplementary Material. 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
 Link to the figure

Process overview

This dataset was generated by the computation detailed below.
Title

Caption for Figure 3.37 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6)
Abstract

ENSO seasonality in observations (black) and historical simulations from CMIP5 (blue; extended with RCP4.5) and CMIP6 (red) for 1951–2010. (a) Climatological standard deviation of the monthly ENSO index (SST anomaly averaged over the Niño 3.4 region; °C). Shading and lines represent 5th–95th percentiles and multi-model ensemble means, respectively. (b) Seasonality metric, which is defined for each model and each ensemble member as the ratio of the ENSO index climatological standard deviation in November–January (NDJ) to that in March–May (MAM). Each dot represents an ensemble member from the model indicated on the vertical axis. The boxes and whiskers represent the multi-model ensemble mean, interquartile ranges and 5th and 95th percentiles of CMIP5 and CMIP6 individually. The CMIP5 and CMIP6 multi-model ensemble means and observational values are indicated at the top right of the panel. The multi-model ensemble means and percentile values are evaluated after weighting individual members with the inverse of the ensemble size of the same model, so that individual models are equally weighted irrespective of their ensemble sizes. All results are based on five-month running mean SST anomalies with triangular-weights after linear detrending. 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
  • units: degrees_C
  • var_id: stdv_enso_obs
  • long_name: Climatological standard deviation of the ENSO index
  • var_id: seasonality_enso_obs
  • long_name: The ratio of the ENSO index climatological standard deviation in NDJ to that in MAM
  • var_id: month
  • units: months
  • long_name: calendar month
  • var_id: dataset
  • var_id: ens_cmip5
  • var_id: ens_cmip6

Co-ordinate Variables

Coverage
Temporal Range
Start time:
1951-01-01T12:00:00
End time:
2010-12-31T12:00:00
Geographic Extent

 
5.0000°
  
-170.0000°
  
-120.0000°
 
-5.0000°
  
Related parties
Authors (4)
Publishers (1)