GloSATLAT.1.0.0.0: An observational record of global surface air temperature change over land from 1781

GloSATLAT is a global gridded data set of surface air temperature change over land since 1781. Data are provided as air temperature anomalies relative to 1961-1990 average conditions on a 5-degree latitude by 5-degree longitude grid. Time series of average temperature changes and their uncertainties are available for the globe and for a selection of regions.

The gridded data set is constructed using meteorological station temperature series from the GloSATLAT station database (GloSATLAT sdb). This is an extended version of the CRUTEM5 station database. The station series include bias adjustments for non-standard thermometer enclosures in the early instrumental period, prior to the use of standard instrumental shelters (Wallis et al., 2024). New climatological normal estimates are included for stations with limited data in the 1961–1990 baseline period, estimated using the Local Expectation Kriging method (Taylor et al., 2025), allowing a larger number of station series to contribute to the gridded data set.

GloSATLAT uses the HadCRUT5 data processing system to produce the gridded data set, time series and uncertainty estimates.

Sources of additional information:
The following papers are provided in the related documents section with further information about GloSATLAT and its underpinning data.

Gridded dataset description:
Morice, C. P., et al. (2025). An observational record of global gridded near surface air temperature change over land and ocean from 1781, Earth Syst. Sci. Data Discuss. https://doi.org/10.5194/essd-2024-500.

Land station data processing:
Taylor, M. et al. (2025, in review). GloSAT LATsdb: a global compilation of land air temperature station records with updated climatological normals from local expectation kriging. Submitted to Geoscience Data Journal.
Wallis, E. J., et al. (2024). Quantifying exposure biases in early instrumental land surface air temperature observations. International Journal of Climatology, 44(5), 1611–1635. https://doi.org/10.1002/joc.8401