Document raw (unassessed) mean temperature anomalies for time periods in cmip5 and cmip6 data. Check the global warming levels repository for a list of the year when a certain global warming level is reached.
Mathias Hauser1
1Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
This data archive is created and maintained in an voluntary effort by its creators. The data are provided without warranty of any kind. Please note that the ownership of all files in the archive remains with the original providers! That means you should still acknowledge the data providers. This work is published under a CC BY-SA 4.0 license by the authors. If you use the this archive please cite 10.5281/zenodo.5532894.
The Working Group I (WGI) contribution to the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) also lists changes in global surface temperature. For example in the Summary for Policymakers (SPM) in Table SPM.1 and Figure SPM.8. The official numbers in the IPCC represent an assessment based on multiple lines of evidence (e.g. observational data is used to perform a model weighting) - see details in the IPCC report. The numbers presented here are only based on the model data.
Table 1: Raw (unassessed) multi-model mean global-mean temperatures for selected time periods and shared socioeconomic pathways (SSPs). Number in brackets indicates number of models in the ensemble. The same information can be found in a csv file cmip6_mmm_temperatures_one_ens_1850_1900.csv.
| period | SSP1-1.9 (14) | SSP1-2.6 (41) | SSP2-4.5 (42) | SSP3-7.0 (35) | SSP5-8.5 (44) |
|---|---|---|---|---|---|
| (°C) | (°C) | (°C) | (°C) | (°C) | |
| 2021-2040 | 1.53 | 1.61 | 1.64 | 1.6 | 1.73 |
| 2041-2060 | 1.67 | 1.95 | 2.19 | 2.31 | 2.63 |
| 2081-2100 | 1.53 | 2.06 | 3.01 | 4.04 | 4.99 |
| 2016-2035 | 1.42 | 1.48 | 1.49 | 1.44 | 1.54 |
| 2046-2065 | 1.67 | 1.99 | 2.33 | 2.51 | 2.88 |
| 2011-2020 | 1.13 | 1.18 | 1.19 | 1.15 | 1.19 |
| 2021-2030 | 1.43 | 1.5 | 1.5 | 1.44 | 1.54 |
| 2031-2040 | 1.63 | 1.72 | 1.78 | 1.77 | 1.92 |
| 2041-2050 | 1.69 | 1.9 | 2.05 | 2.11 | 2.38 |
| 2051-2060 | 1.66 | 1.99 | 2.34 | 2.51 | 2.88 |
| 2061-2070 | 1.64 | 2.05 | 2.54 | 2.92 | 3.43 |
| 2071-2080 | 1.6 | 2.08 | 2.76 | 3.35 | 4.02 |
| 2081-2090 | 1.57 | 2.07 | 2.94 | 3.82 | 4.67 |
| 2091-2100 | 1.5 | 2.04 | 3.08 | 4.27 | 5.31 |
Table 2: Raw (unassessed) multi-model mean global-mean temperatures for selected time periods and representative concentration pathways (RCPs). Number in brackets indicates number of models in the ensemble. The same information can be found in a csv file cmip5_mmm_temperatures_one_ens_1850_1900.csv.
| period | RCP2.6 (21) | RCP4.5 (30) | RCP6.0 (14) | RCP8.5 (32) |
|---|---|---|---|---|
| (°C) | (°C) | (°C) | (°C) | |
| 2021-2040 | 1.53 | 1.56 | 1.46 | 1.71 |
| 2041-2060 | 1.72 | 2 | 1.86 | 2.49 |
| 2081-2100 | 1.69 | 2.49 | 2.83 | 4.36 |
| 2016-2035 | 1.44 | 1.44 | 1.36 | 1.54 |
| 2046-2065 | 1.72 | 2.09 | 1.95 | 2.71 |
| 2011-2020 | 1.25 | 1.2 | 1.18 | 1.24 |
| 2021-2030 | 1.46 | 1.44 | 1.36 | 1.54 |
| 2031-2040 | 1.61 | 1.68 | 1.55 | 1.87 |
| 2041-2050 | 1.71 | 1.9 | 1.76 | 2.27 |
| 2051-2060 | 1.72 | 2.09 | 1.95 | 2.71 |
| 2061-2070 | 1.73 | 2.25 | 2.17 | 3.18 |
| 2071-2080 | 1.7 | 2.38 | 2.46 | 3.65 |
| 2081-2090 | 1.69 | 2.47 | 2.74 | 4.12 |
| 2091-2100 | 1.68 | 2.51 | 2.92 | 4.61 |
Temperature anomalies for individual models can be found in separate folders for cmip6 and cmip5
The data is available in csv files:
model, ens, exp, postprocess, table, grid, varn, period, mean
CAMS-CSM1-0, r1i1p1f1, ssp119, global_mean, Amon, gn, tas, 2021-2040, 1.07
CNRM-ESM2-1, r1i1p1f2, ssp119, global_mean, Amon, gr, tas, 2021-2040, 1.32
CanESM5, r1i1p1f1, ssp119, global_mean, Amon, gn, tas, 2021-2040, 2.16
...
There are two files with cmip6 data. One with one ensemble member per model and one with all ensemble members. For cmip5 two additional files are provided. The reference period is 1850 to 1900, however, many cmip5 models only start after 1850 and are therefore excluded. These models are also included in the *_no_bounds_check.yml files.
- Monthly temperature data (variable:
tas, Table ID:Lmon) forhistoricalandRCP2.6,RCP4.5,RCP6.0, andRCP8.5(CMIP5)SSP1-1.9,SSP1-2.6,SSP2-4.5,SSP3-7.0, andSSP5-8.5(CMIP6)
- Grid-cell area for atmospheric grid variables (
areacella)
To calculate the temperature anomalies the following method is used for every individual model:
- Calculate global mean temperature (weighted with the grid cell area (
areacella) if available, else thecosof the latitude is used) - Calculate annual mean (Note: all months are weighted equally)
- Concatenate historical data and projection (constrained to the historical/ future time period)
- Subtract the mean over 1850 to 1900 (inclusive)
- Calculate the mean over the indicated time period
The code is available under https://github.com/IPCC-WG1/Chapter-11/tree/main/code/cmip_temperatures.ipynb.
The changelog of the repository can be found under CHANGELOG.md.
CMIP TEMPERATURES is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
A copy of the license is availabe at LICENSE. If not, see CC BY-SA 4.0.
The underlying raw data are published under the license of CMIP5. Terms of use for CMIP5 are applied for the derived data presented here. They are provided at https://pcmdi.llnl.gov/mips/cmip5/terms-of-use.html. Data from some modelling centres are licensed for use in non-commercial research and for educational purposes, other for unrestricted use. Please refer to the terms of use for the CMIP5 modeling groups for details. The data should be cited by its DOI and according to the citation recommendation of CMIP5.
The raw CMIP6 data are licensed under Creative Commons CC BY-SA 4.0, following the CMIP6 Terms of Use. Note that some models publish the data under a non-commercial license (CC BY-NC-SA 4.0). The license for each particular model dataset can be obtained at the ESGF CoG portal as part of the data citation information.
We thank Urs Beyerle for downloading and curating the CMIP5 and CMIP6 data at the Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland.
We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in cmip5_models.md) for producing and making available their model output. For CMIP the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.”
We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF.