Global Temperature Time Series. 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 from 1880 to the present.
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 [...].
- 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).
- Name: GISTEMP Global Land-Ocean Temperature Index
- Web: http://data.giss.nasa.gov/gistemp
- Name: Global component of Climate at a Glance (GCAG)
- Web: http://www.ncdc.noaa.gov/cag/data-info/global
- Upstream datasets:
Data preparation requires Python 2.
Run the following script from this directory to download and process the data:
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.
The raw data are output to
./tmp. The processed data are output to
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/
The upstream datasets do not impose any specific restrictions on using these data in a public or commercial product: