This dataset contains daily land surface temperatures (LSTs) and their uncertainty estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Earth Observing System – Terra (Terra). Satellite land surface temperatures are skin temperatures which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.

Daytime and night-time temperatures are provided in separate files corresponding to the morning and evening Terra equator crossing times which are 10:30 and 22:30 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class.

The dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. MODIS achieves full Earth coverage nearly twice per day so the daily files have small gaps primarily close to the equator where the surface is not covered by the satellite swath on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface.

The daily dataset starts from 24th February 2000 and ends 31st December 2021. There are minor interruptions (1-2 days) during satellite/instrument maintenance periods.

In Version 4.00 the time series has been extended to 2021. The emissivities used in the retrieval come from the Combined ASTER and MODIS Emissivity over Land (CAMEL) Version 2 database; in Version 4.00 a climatology is used since there are temporal instabilities in the CAMEL time series.

The dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using a generalised split window retrieval algorithm and data were processed in the UoL processing chain.

The dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards.