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Start with these files — they give you everything you need to understand and access the dataset.
- 1. Fetch datapackage.json to inspect schema and resources
- 2. Download data resources listed in datapackage.json
- 3. Read README.md for full context
Data Views
Data Previews
annual
Schema
| name | type | description |
|---|---|---|
| Source | string | |
| Year | year | YYYY |
| Mean | number | Average global mean temperature anomalies in degrees Celsius relative to a base period. GISTEMP base period: 1951-1980. GCAG base period: 20th century average. |
monthly
Schema
| name | type | format | description |
|---|---|---|---|
| Source | string | ||
| Year | date | any | YYYY-MM |
| Mean | number | Monthly mean temperature anomalies in degrees Celsius relative to a base period. GISTEMP base period: 1951-1980. GCAG base period: 20th century average. |
Data Files
| File | Description | Size | Last modified | Download |
|---|---|---|---|---|
annual | 6.33 kB | 27 days ago | annual | |
monthly | 83.9 kB | 27 days ago | monthly |
| Files | Size | Format | Created | Updated | License | Source |
|---|---|---|---|---|---|---|
| 2 | 90.3 kB | csv | 1 day ago | Open Data Commons Public Domain Dedication and License v1.0 | GISTEMP Global Land-Ocean Temperature Index |
Data are included from the GISS Surface Temperature (GISTEMP) analysis and the global component of Climate at a Glance (GCAG). Two datasets are provided: 1) global monthly mean and 2) annual mean temperature anomalies in degrees Celsius. The GISTEMP data are available from 1880 to the present, while the GCAG data are available from 1850 to the present.
Data
Description
Combined Land-Surface Air and Sea-Surface Water Temperature Anomalies [i.e. deviations from the corresponding 1951-1980 means]. Global-mean monthly […] and annual means, 1880-present, updated through most recent month.
Global temperature anomaly data come from the Global Historical Climatology Network-Monthly (GHCN-M) data set and International Comprehensive Ocean-Atmosphere Data Set (ICOADS), which have data from 1880 to the present. These two datasets are blended into a single product to produce the combined global land and ocean temperature anomalies. The available timeseries of global-scale temperature anomalies are calculated with respect to the 20th century average […].
Citations
- GISTEMP: NASA Goddard Institute for Space Studies (GISS) Surface Temperature Analysis, Global Land-Ocean Temperature Index.
- NOAA National Climatic Data Center (NCDC), global component of Climate at a Glance (GCAG).
Sources
- Name: GISTEMP Global Land-Ocean Temperature Index
- Web: https://data.giss.nasa.gov/gistemp/
- Name: Global component of Climate at a Glance (GCAG)
- Web: https://www.metoffice.gov.uk/hadobs/hadcrut5/data/HadCRUT.5.0.2.0/download.html
Additional Data
Preparation
Requirements
Python 3 is required for data preparation.
Processing
Locally
Run the following script from this directory to download and process the data:
make data
Automated Workflow
Current script is automated using Github Workflows
Hundredths of degrees Celsius in the GISTEMP Global Land-Ocean Temperature Index data are converted to degrees Celsius.
A HadCRUT4 processing script is available but not run by default.
Resources
The processed data are output to ./data.
License
ODC-PDDL-1.0
This Data Package and these datasets are made available under the Public Domain Dedication and License v1.0 whose full text can be found at: http://www.opendatacommons.org/licenses/pddl/1.0/
References
-
Morice, C. P., Kennedy, J. J., Rayner, N. A., Winn, J. P., Hogan, E., Killick, R. E., et al. (2021). An updated assessment of near-surface temperature change from 1850: the HadCRUT5 data set. Journal of Geophysical Research: Atmospheres, 126, e2019JD032361. https://doi.org/10.1029/2019JD032361
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GISTEMP Team. (2024). GISS Surface Temperature Analysis (GISTEMP), version 4. NASA Goddard Institute for Space Studies. Dataset accessed 20YY-MM-DD at https://data.giss.nasa.gov/gistemp/.
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Lenssen, N., Schmidt, G. A., Hendrickson, M., Jacobs, P., Menne, M., & Ruedy, R. (2024). A GISTEMPv4 observational uncertainty ensemble. Journal of Geophysical Research: Atmospheres, 129(17), e2023JD040179. https://doi.org/10.1029/2023JD040179.
Notes
The upstream datasets do not impose any specific restrictions on using these data in a public or commercial product: