Taylor, Michael, Osborn, Timothy J., Cowtan, Kathryn, Morice, Colin P., Jones, Philip D., Wallis, Emily J. and Lister, David H. (2025) GloSAT LATsdb: A Global Compilation of Land Air Temperature Station Records With Updated Climatological Normals From Local Expectation Kriging. Geoscience Data Journal, 12 (4). ISSN 2049-6060
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Abstract
To accurately determine multi-centennial trends in climate data records of the Earth's surface temperature, measurements are commonly analysed in the form of anomalies relative to a climatological reference period such as the World Meteorological Organization (WMO) 1961–1990 baseline. One of many climate-monitoring challenges is that weather records of land surface temperature can be short, typically of the order of several years or decades, and often do not sufficiently overlap the reference period to allow calculation of the climatological normals needed to convert the observations to anomalies. Moreover, the volume of records of this type is increasing due to the rescue of early (pre-baseline) instrumental paper-based records and the growing prevalence of newer (post-baseline) weather stations. To address this, we apply a method to estimate the climatological normal for each calendar month of temperature time series that do not have sufficient data during the baseline period, using an approximation to local expectation kriging with station holdout (LEK). This exploits the information in neighbouring time series to estimate the expected mean level of short series of observations. We apply the method to a global database of monthly land air temperature at 11865 stations based on CRUTEM5 but with the acquisition of an additional 1233 station series including some that extend back to 1781, and with mid-latitude stations adjusted for exposure bias arising from the transition to Stevenson screens. We evaluate the LEK-based normals using climatological normals calculated directly from the station observations. Using this method, we obtain estimated normals for 2699 stations that did not previously have normals and we improve the estimated normals for a further 2611 which had previously been estimated from incomplete data. Finally, we demonstrate how incorporating these thousands of previously unused station observation fragments affects hemispheric temperature averages. Pre-1850 data—primarily from Europe—show a modest warming trend but pronounced multidecadal variability that is greater than after 1850. The additional stations improve spatial coverage by a few percent in recent decades and raise pre-1860 Northern Hemisphere temperature estimates by approximately 0.1°C.
Item Type: | Article |
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Additional Information: | Dataset Details: This dataset is called GloSAT (Global Surface Air Temperature) LAT (land air temperature) sdb (station database), and comprises monthly mean temperature observations and climatological normals for meteorological stations worldwide. This release, v1.0, contains data for 11,865 stations and extends the CRUTEM5 1850–2021 station data (Osborn et al. 2021) back to 1781. Mid-latitude stations have been adjusted to compensate for some thermometer exposure changes. Many stations with either no data or incomplete data during the 1961–1990 baseline period have their climatological normals and standard deviations estimated via a kriging algorithm. The dataset is available from Zenodo at doi.org/10.5281/zenodo.14888902 and the Climatic Research Unit at crudata.uea.ac.uk. Funding: This work was supported by Natural Environment Research Council (NE/S015582/1 and NE/S015566/1). |
Faculty \ School: | Faculty of Science > School of Environmental Sciences University of East Anglia Research Groups/Centres > Theme - ClimateUEA |
UEA Research Groups: | Faculty of Science > Research Groups > Climatic Research Unit Faculty of Science > Research Groups > Centre for Ocean and Atmospheric Sciences Faculty of Social Sciences > Research Centres > Water Security Research Centre |
Depositing User: | LivePure Connector |
Date Deposited: | 11 Aug 2025 15:30 |
Last Modified: | 13 Aug 2025 01:18 |
URI: | https://ueaeprints.uea.ac.uk/id/eprint/100126 |
DOI: | 10.1002/gdj3.70024 |
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