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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
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annual
Schema
| name | type | format | description |
|---|---|---|---|
| Year | date | any | YYYY |
| Land | number | Global annual anomalies computed from land data, in degrees C | |
| Land and Ocean | number | Global annual anomalies computed from land and ocean data, in degrees C | |
| N Hem | number | Northern hemisphere annual anomalies computed from land and ocean data, in degrees C | |
| S Hem | number | Southern hemisphere annual anomalies computed from land and ocean data, in degrees C | |
| Band 1 | number | Latitude band (90N-23.6N, 30% of global area) annual anomalies computed from land and ocean data, in degrees C | |
| Band 2 | number | Latitude band (23.6N-23.6S, 40% of global area) annual anomalies computed from land and ocean data, in degrees C | |
| Band 3 | number | Latitude band (23.6S-90S, 30% of global area) annual anomalies computed from land and ocean data, in degrees C |
global-temp-5yr
Schema
| name | type | format | description |
|---|---|---|---|
| Year | date | any | YYYY |
| Land | number | Global 5-year anomalies mean computed from land data, in degrees C | |
| Land and Ocean | number | Global 5-year anomalies mean computed from land and ocean data, in degrees C | |
| N Hem | number | Northern hemisphere 5-year anomalies mean computed from land and ocean data, in degrees C | |
| S Hem | number | Southern hemisphere 5-year anomalies mean computed from land and ocean data, in degrees C | |
| Band 1 | number | Latitude band (90N-23.6N, 30% of global area) 5-year anomalies mean computed from land and ocean data, in degrees C | |
| Band 2 | number | Latitude band (23.6N-23.6S, 40% of global area) 5-year anomalies mean computed from land and ocean data, in degrees C | |
| Band 3 | number | Latitude band (23.6S-90S, 30% of global area) 5-year anomalies mean computed from land and ocean data, in degrees C |
Data Files
| File | Description | Size | Last modified | Download |
|---|---|---|---|---|
annual | 5.73 kB | about 1 month ago | annual | |
global-temp-5yr | 5.63 kB | about 1 month ago | global-temp-5yr |
| Files | Size | Format | Created | Updated | License | Source |
|---|---|---|---|---|---|---|
| 2 | 11.4 kB | csv | 5 days ago | Open Data Commons Public Domain Dedication and License v1.0 | Global Annual Temperature Anomalies (Land), 1880-2014 |
⚠️⚠️⚠️ DATA HAS BEEN DEPRECATED ⚠️⚠️⚠️
Nasa GISS Surface Temperature (GISTEMP) Analysis. Four different series are provided: Global Annual Temperature Anomalies (Land) 1880-2014, Global Annual Temperature Anomalies (Land and Ocean) 1880-2014, Hemispheric Temperature Anomalies (Land+ Ocean) 1880-2014 and Annual Temperature anomalies (Land + Ocean) for three latitude bands that cover 30%, 40% and 30% of the global area, respectively, 1900-2014.
Data
Period of Record
1880-2014 (Anomalies are relative to the 1951-80 base period means.)
Description
The NASA GISS Surface Temperature (GISTEMP) analysis provides a measure of the changing global surface temperature with monthly resolution for the period since 1880, when a reasonably global distribution of meteorological stations was established. The input data Ruedy et al. use for the analysis, collected by many national meteorological services around the world, are the adjusted data of the Global Historical Climatology Network (GHCN) Vs. 3 (this represents a change from prior use of unadjusted Vs. 2 data) (Peterson and Vose, 1997 and 1998), United States Historical Climatology Network (USHCN) data, and SCAR (Scientific Committee on Antarctic Research) data from Antarctic stations. Documentation of the basic analysis method is provided by Hansen et al. (1999), with several modifications described by Hansen et al. (2001). The GISS analysis is updated monthly, however CDIAC's presentation of the data here is updated annually.
Key finding
The global mean temperature for 2014 was the warmest on record (see Trends section for further details)
Sources
- Name: Global Annual Temperature Anomalies (Land), 1880-2014
- Web: http://cdiac.ornl.gov/ftp/trends/temp/hansen/gl_land.txt
- Name: Global Annual Temperature Anomalies (Land+Ocean), 1880-2014
- Web: http://cdiac.ornl.gov/ftp/trends/temp/hansen/gl_land_ocean.txt
- Name: Hemispheric Temperature Anomalies (Land+Ocean), 1880-2014
- Web: http://cdiac.ornl.gov/ftp/trends/temp/hansen/nhsh.txt
- Name: Global Annual Temperature Anomalies (Land+Ocean) for three latitude bands, 1900-2014
- Web: http://cdiac.ornl.gov/ftp/trends/temp/hansen/norlowsou.txt
Preparation
Requirements
Python 2 together with modules urllib and csv are required in order to process the data.
Processing
Run the following script from this directory to download and process the data:
make
Resources
The raw data are stored in ./archive/. The processed data can be found in ./data.
License
Data
Data are sourced from US Federal government funded agency and no copyright restrictions are applied. More specifically:
If you wish to use a diagram, image, graph, table, or other materials from the CDIAC website and are concerned with obtaining permission and possible copyright restrictions, there should be no concerns. All of the reports, graphics, data, and other information on the CDIAC website are freely and publicly available without copyright restrictions.*
Additional work
All the additional work made to build this Data Package is 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/
Citations
Ruedy, R., M. Sato, and K. Lo. 2015. NASA GISS Surface Temperature (GISTEMP) Analysis. In Trends: A Compendium of Data on Global Change. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A. doi: 10.3334/CDIAC/cli.001 .