Dataset
Chapter 10 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 10.10 (v20220622)
Abstract
Data for Figure 10.10 from Chapter 10 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).
Figure 10.10 shows observed and projected changes in austral summer (December to February) mean precipitation in Global Precipitation Climatology Centre (GPCC), Climatic Research Unit Time-Series (CRU TS) and 100 members of the Max-Planck-Institut für Meteorologie Earth-System Model (MPI-ESM).
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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:
Doblas-Reyes, F.J., A.A. Sörensson, M. Almazroui, A. Dosio, W.J. Gutowski, R. Haarsma, R. Hamdi, B. Hewitson, W.-T. Kwon, B.L. Lamptey, D. Maraun, T.S. Stephenson, I. Takayabu, L. Terray, A. Turner, and Z. Zuo, 2021: Linking Global to Regional Climate Change. 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. 1363–1512, doi:10.1017/9781009157896.012.
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Figure subpanels
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The figure has two panels, with data provided for both panels. Panel (a) consists of two maps, panel (b) shows multiple timeseries and boxplots.
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List of data provided
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The dataset contains data of relative precipitation anomalies over 1950-2100 with respect to 1995-2014 average for global, S.E.South-America, Sao Paulo and Buenos Aires for:
- Observational data (GPCC and CRU TS)
- Model data (100 runs of MPI-ESM)
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Data provided in relation to figure
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Panel (a):
- Data files:
Modelled precipitation rate OLS linear trends between 2015-2070 with respect to 1995-2014 average over S.E. South America region, from left to right (MPI-ESM member with min (driest) and max (wettest) trends):
Fig_10_10_panel-a_mapplot_trend_SES_DJF_MPI-GE_min_single-MultiModelMean_trend-min-median-max.nc,
Fig_10_10_panel-a_mapplot_trend_SES_DJF_MPI-GE_max_single-MultiModelMean_trend-min-median-max.nc
Panel (b):
- Data files:
Precipitation rate anomalies 1950-2100 with respect to 1995-2014 average for the global mean, S.E.South-America mean, Sao Paulo mean and Buenos Aires mean of GPCC (dark blue), CRU (dark brown), members of the MPI-ESM (grey), the MPI-ESM member with the driest (brown) and wettest (green) trend:
Fig_10_10_panel-b_timeseries_global.csv,
Fig_10_10_panel-b_timeseries_SES.csv,
Fig_10_10_panel-b_timeseries_SaoPaulo.csv,
Fig_10_10_panel-b_timeseries_BuenosAires.csv
- Data files:
Underlying data points of the boxplot showing MPI-ESM modelled precipitation rate OLS linear trends over all members between 2015-2070 with respect to 1995-2014 average for the global mean, S.E.South-America mean, Sao Paulo mean and Buenos Aires mean:
Fig_10_10_panel-b_boxplot_BuenosAires.csv,
Fig_10_10_panel-b_boxplot_global.csv,
Fig_10_10_panel-b_boxplot_SaoPaulo.csv,
Fig_10_10_panel-b_boxplot_SES.csv;
OLS - ordinary least squares regression.
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Notes on reproducing the figure from the provided data
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The code for ESMValTool is provided.
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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 figure on the IPCC AR6 website
- Link to the report component containing the figure (Chapter 10)
- Link to the Supplementary Material for Chapter 10, which contains details on the input data used in Table 10.SM.11
- Link to the code for the figure, archived on Zenodo.
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(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
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| File Format: |
txt, netCDF, csv
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Related Documents
Process overview
| Title | Caption for Figure 10.10 from Chapter 10 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6) |
| Abstract | Observed and projected changes in austral summer (December to February) mean precipitation in Global Precipitation Climatoloy Centre (GPCC), Climatic Research Unit Time Series (CRU TS) and 100 members of the Max Planck Institute for Meteorology Earth System Model (MPI-ESM. (a) 55-year trends (2015‒2070) from the ensemble members with the lowest (left) and highest (right) trend (% per decade, baseline 1995–2014). (b) Time series (%, baseline 1995–2014) for different spatial scales (from top to bottom: global averages; South-Eastern South America; grid boxes close to São Paulo and Buenos Aires) with a five-point weighted running mean applied (a variant on the binomial filter with weights [1-3-4-3-1]). The brown (green) lines correspond to the ensemble member with weakest (strongest) 55-year trend and the grey lines to all remaining ensemble members. Box-and-whisker plots show the distribution of 55-year linear trends across all ensemble members, and follow the methodology used in Figure 10.6. Trends are estimated using ordinary least squares. Further details on data sources and processing are available in the chapter data table (Table 10.SM.11). |
| Input Description | None |
| Output Description | None |
| Software Reference | None |
- units: %
- var_id: 2
- long_name: CRU TS - Precipitation relative anomaly
- units: %
- var_id: 3
- long_name: GPCC - Precipitation relative anomaly
- units: %
- var_id: 5
- long_name: MPI-ESM max - Precipitation relative anomaly
- units: %
- var_id: 4
- long_name: MPI-ESM min - Precipitation relative anomaly
- units: %
- var_id: 6
- long_name: MPI-ESM run1 - Precipitation relative anomaly
- units: %
- var_id: 2
- long_name: MPI-ESM run1-100 trend
- units: %
- var_id: 7
- long_name: MPI-ESM run10 - Precipitation relative anomaly
- units: %
- var_id: 8
- long_name: MPI-ESM run100 - Precipitation relative anomaly
- units: %
- var_id: 9
- long_name: MPI-ESM run11 - Precipitation relative anomaly
- units: %
- var_id: 10
- long_name: MPI-ESM run12 - Precipitation relative anomaly
- units: %
- var_id: 11
- long_name: MPI-ESM run13 - Precipitation relative anomaly
- units: %
- var_id: 12
- long_name: MPI-ESM run14 - Precipitation relative anomaly
- units: %
- var_id: 13
- long_name: MPI-ESM run15 - Precipitation relative anomaly
- units: %
- var_id: 14
- long_name: MPI-ESM run16 - Precipitation relative anomaly
- units: %
- var_id: 15
- long_name: MPI-ESM run17 - Precipitation relative anomaly
- units: %
- var_id: 16
- long_name: MPI-ESM run18 - Precipitation relative anomaly
- units: %
- var_id: 17
- long_name: MPI-ESM run19 - Precipitation relative anomaly
- units: %
- var_id: 18
- long_name: MPI-ESM run2 - Precipitation relative anomaly
- units: %
- var_id: 19
- long_name: MPI-ESM run20 - Precipitation relative anomaly
- units: %
- var_id: 20
- long_name: MPI-ESM run21 - Precipitation relative anomaly
- units: %
- var_id: 21
- long_name: MPI-ESM run22 - Precipitation relative anomaly
- units: %
- var_id: 22
- long_name: MPI-ESM run23 - Precipitation relative anomaly
- units: %
- var_id: 23
- long_name: MPI-ESM run24 - Precipitation relative anomaly
- units: %
- var_id: 24
- long_name: MPI-ESM run25 - Precipitation relative anomaly
- units: %
- var_id: 25
- long_name: MPI-ESM run26 - Precipitation relative anomaly
- units: %
- var_id: 26
- long_name: MPI-ESM run27 - Precipitation relative anomaly
- units: %
- var_id: 27
- long_name: MPI-ESM run28 - Precipitation relative anomaly
- units: %
- var_id: 28
- long_name: MPI-ESM run29 - Precipitation relative anomaly
- units: %
- var_id: 29
- long_name: MPI-ESM run3 - Precipitation relative anomaly
- units: %
- var_id: 30
- long_name: MPI-ESM run30 - Precipitation relative anomaly
- units: %
- var_id: 31
- long_name: MPI-ESM run31 - Precipitation relative anomaly
- units: %
- var_id: 32
- long_name: MPI-ESM run32 - Precipitation relative anomaly
- units: %
- var_id: 33
- long_name: MPI-ESM run33 - Precipitation relative anomaly
- units: %
- var_id: 34
- long_name: MPI-ESM run34 - Precipitation relative anomaly
- units: %
- var_id: 35
- long_name: MPI-ESM run35 - Precipitation relative anomaly
- units: %
- var_id: 36
- long_name: MPI-ESM run36 - Precipitation relative anomaly
- units: %
- var_id: 37
- long_name: MPI-ESM run37 - Precipitation relative anomaly
- units: %
- var_id: 38
- long_name: MPI-ESM run38 - Precipitation relative anomaly
- units: %
- var_id: 39
- long_name: MPI-ESM run39 - Precipitation relative anomaly
- units: %
- var_id: 40
- long_name: MPI-ESM run4 - Precipitation relative anomaly
- units: %
- var_id: 41
- long_name: MPI-ESM run40 - Precipitation relative anomaly
- units: %
- var_id: 42
- long_name: MPI-ESM run41 - Precipitation relative anomaly
- units: %
- var_id: 43
- long_name: MPI-ESM run42 - Precipitation relative anomaly
- units: %
- var_id: 44
- long_name: MPI-ESM run43 - Precipitation relative anomaly
- units: %
- var_id: 45
- long_name: MPI-ESM run44 - Precipitation relative anomaly
- units: %
- var_id: 46
- long_name: MPI-ESM run45 - Precipitation relative anomaly
- units: %
- var_id: 47
- long_name: MPI-ESM run46 - Precipitation relative anomaly
- units: %
- var_id: 48
- long_name: MPI-ESM run47 - Precipitation relative anomaly
- units: %
- var_id: 49
- long_name: MPI-ESM run48 - Precipitation relative anomaly
- units: %
- var_id: 50
- long_name: MPI-ESM run49 - Precipitation relative anomaly
- units: %
- var_id: 51
- long_name: MPI-ESM run5 - Precipitation relative anomaly
- units: %
- var_id: 52
- long_name: MPI-ESM run50 - Precipitation relative anomaly
- units: %
- var_id: 53
- long_name: MPI-ESM run51 - Precipitation relative anomaly
- units: %
- var_id: 54
- long_name: MPI-ESM run52 - Precipitation relative anomaly
- units: %
- var_id: 55
- long_name: MPI-ESM run53 - Precipitation relative anomaly
- units: %
- var_id: 56
- long_name: MPI-ESM run54 - Precipitation relative anomaly
- units: %
- var_id: 57
- long_name: MPI-ESM run55 - Precipitation relative anomaly
- units: %
- var_id: 58
- long_name: MPI-ESM run56 - Precipitation relative anomaly
- units: %
- var_id: 59
- long_name: MPI-ESM run57 - Precipitation relative anomaly
- units: %
- var_id: 60
- long_name: MPI-ESM run58 - Precipitation relative anomaly
- units: %
- var_id: 61
- long_name: MPI-ESM run59 - Precipitation relative anomaly
- units: %
- var_id: 62
- long_name: MPI-ESM run6 - Precipitation relative anomaly
- units: %
- var_id: 63
- long_name: MPI-ESM run60 - Precipitation relative anomaly
- units: %
- var_id: 64
- long_name: MPI-ESM run61 - Precipitation relative anomaly
- units: %
- var_id: 65
- long_name: MPI-ESM run62 - Precipitation relative anomaly
- units: %
- var_id: 66
- long_name: MPI-ESM run63 - Precipitation relative anomaly
- units: %
- var_id: 67
- long_name: MPI-ESM run64 - Precipitation relative anomaly
- units: %
- var_id: 68
- long_name: MPI-ESM run65 - Precipitation relative anomaly
- units: %
- var_id: 69
- long_name: MPI-ESM run66 - Precipitation relative anomaly
- units: %
- var_id: 70
- long_name: MPI-ESM run67 - Precipitation relative anomaly
- units: %
- var_id: 71
- long_name: MPI-ESM run68 - Precipitation relative anomaly
- units: %
- var_id: 72
- long_name: MPI-ESM run69 - Precipitation relative anomaly
- units: %
- var_id: 73
- long_name: MPI-ESM run7 - Precipitation relative anomaly
- units: %
- var_id: 74
- long_name: MPI-ESM run70 - Precipitation relative anomaly
- units: %
- var_id: 75
- long_name: MPI-ESM run71 - Precipitation relative anomaly
- units: %
- var_id: 76
- long_name: MPI-ESM run72 - Precipitation relative anomaly
- units: %
- var_id: 77
- long_name: MPI-ESM run73 - Precipitation relative anomaly
- units: %
- var_id: 78
- long_name: MPI-ESM run74 - Precipitation relative anomaly
- units: %
- var_id: 79
- long_name: MPI-ESM run75 - Precipitation relative anomaly
- units: %
- var_id: 80
- long_name: MPI-ESM run76 - Precipitation relative anomaly
- units: %
- var_id: 81
- long_name: MPI-ESM run77 - Precipitation relative anomaly
- units: %
- var_id: 82
- long_name: MPI-ESM run78 - Precipitation relative anomaly
- units: %
- var_id: 83
- long_name: MPI-ESM run79 - Precipitation relative anomaly
- units: %
- var_id: 84
- long_name: MPI-ESM run8 - Precipitation relative anomaly
- units: %
- var_id: 85
- long_name: MPI-ESM run80 - Precipitation relative anomaly
- units: %
- var_id: 86
- long_name: MPI-ESM run81 - Precipitation relative anomaly
- units: %
- var_id: 87
- long_name: MPI-ESM run82 - Precipitation relative anomaly
- units: %
- var_id: 88
- long_name: MPI-ESM run83 - Precipitation relative anomaly
- units: %
- var_id: 89
- long_name: MPI-ESM run84 - Precipitation relative anomaly
- units: %
- var_id: 90
- long_name: MPI-ESM run85 - Precipitation relative anomaly
- units: %
- var_id: 91
- long_name: MPI-ESM run86 - Precipitation relative anomaly
- units: %
- var_id: 92
- long_name: MPI-ESM run87 - Precipitation relative anomaly
- units: %
- var_id: 93
- long_name: MPI-ESM run88 - Precipitation relative anomaly
- units: %
- var_id: 94
- long_name: MPI-ESM run89 - Precipitation relative anomaly
- units: %
- var_id: 95
- long_name: MPI-ESM run9 - Precipitation relative anomaly
- units: %
- var_id: 96
- long_name: MPI-ESM run90 - Precipitation relative anomaly
- units: %
- var_id: 97
- long_name: MPI-ESM run91 - Precipitation relative anomaly
- units: %
- var_id: 98
- long_name: MPI-ESM run92 - Precipitation relative anomaly
- units: %
- var_id: 99
- long_name: MPI-ESM run93 - Precipitation relative anomaly
- units: %
- var_id: 100
- long_name: MPI-ESM run94 - Precipitation relative anomaly
- units: %
- var_id: 101
- long_name: MPI-ESM run95 - Precipitation relative anomaly
- units: %
- var_id: 102
- long_name: MPI-ESM run96 - Precipitation relative anomaly
- units: %
- var_id: 103
- long_name: MPI-ESM run97 - Precipitation relative anomaly
- units: %
- var_id: 104
- long_name: MPI-ESM run98 - Precipitation relative anomaly
- units: %
- var_id: 105
- long_name: MPI-ESM run99 - Precipitation relative anomaly
- units: %
- var_id: pr
- standard_name: precipitation_flux
- long_name: Precipitation relative anomaly
- long_name: Year
- units: Year
- var_id: 1
- long_name: clim_season
- var_id: clim_season
- var_id: 1
- long_name: ensemble member
- units: ensemble member
- var_id: lat_bnds
- var_id: lon_bnds
- units: 1
- long_name: season_year
- var_id: season_year
- var_id: season_year_bnds
- var_id: time_bnds
- units: 1
- long_name: year
- var_id: year
- var_id: year_bnds
Co-ordinate Variables
- units: degrees_north
- standard_name: latitude
- long_name: latitude
- var_id: lat
- units: degrees_east
- standard_name: longitude
- long_name: longitude
- var_id: lon
- long_name: time
- standard_name: time
- var_id: time
- units: days
Temporal Range
1950-01-01T12:00:00
2100-12-31T12:00:00
Geographic Extent
90.0000° |
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-180.0000° |
180.0000° |
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-90.0000° |