GloSAT will develop a longer and more consistent global surface air temperature climate record, and improve our understanding of climate change since the late 18th century. This will involve three key objectives:

1) An extension of the global surface air temperature record.

This extension requires digitisation of new data sources, which will be achieved through a combination of citizen-science networks, specialist input and improvements to automatic text recognition systems. These new data will be combined with existing archives. For the marine archive we propose to use machine learning techniques to identify and correct mispositioned data from particular ships. Methodological improvements are needed to better characterise sources of warm biases in air temperature measurements, particularly those taken in sunny conditions on ships, and before 1850 for measurements over both land and ocean. Once adjusted for biases, referenced to a common height above the surface, and characterised with uncertainty estimates, the observations will be used to construct gridded datasets of air temperature separately for land and ocean regions, all with estimates of their uncertainty and its correlation structure.

2) The construction and evaluation of a consistent global surface air temperature record.

The temperature records will be assessed for consistency. Internal consistency will be assessed for land and ocean fields separately. Automatic "break-point" detection methods will be applied to air temperature observations from land stations, and measurements from coastal stations will be used to evaluate marine air temperatures. Evaluation will then extend to understanding differences between the land, sea and ice-covered regions and model how the differences across boundaries are expected to vary, for example with wind direction. This new knowledge will be incorporated into the global gridded fields of air temperature. This global analysis builds on dataset-construction techniques developed as part of the EU-funded EUSTACE project.

3) Exploiting GloSAT to better understand our changing climate.

This new, longer and more consistent dataset will better characterize pre-industrial temperature variations, allowing an improved understanding of the relationship between human-induced and natural climate variability and a better constraint on the emerging global warming signal. A particular focus will be on analysing and understanding decadal variations in the Atlantic and connected land regions to resolve fundamental questions about the drivers of decadal and multi-decadal variability. El Nino Southern Oscillation (ENSO) events and longer timescale Pacific variability will also be explored.