posted on 2018-01-10, 11:17authored byD. J. Ghent, G. K. Corlett, F. M. Göttsche, J. J. Remedios
The Leicester Along-Track Scanning Radiometer (ATSR) and Sea and Land Surface Temperature Radiometer (SLSTR) Processor for LAnd Surface Temperature (LASPLAST) provides global land surface temperature (LST) products from thermal infrared radiance data. In this paper, the state-of-the-art version of LASPLAST, as deployed in the GlobTemperature project, is described and applied to data from the Advanced Along-Track Scanning Radiometer (AATSR). The LASPLAST retrieval formulation for LST is a nadir-only, two-channel, split-window algorithm, based on biome classification, fractional vegetation, and across-track water vapor dependences. It incorporates globally robust retrieval coefficients derived using highly sampled atmosphere profiles. LASPLAST benefits from appropriate spatial resolution auxiliary information and a new probabilistic-based cloud flagging algorithm. For the first time for a satellite-derived LST product, pixel-level uncertainties characterized in terms of random, locally correlated, and systematic components are provided. The new GlobTemperature GT_ATS_2P Version 1.0 product has been validated for 1 year of AATSR data (2009) against in situ measurements acquired from "gold standard reference" stations: Gobabeb, Namibia, and Evora, Portugal; seven Surface Radiation Budget stations, and the Atmospheric Radiation Measurement station at Southern Great Plains. These data show average absolute biases for the GT_ATS_2P Version 1.0 product of 1.00 K in the daytime and 1.08 K in the nighttime. The improvements in data provenance including better accuracy, fully traceable retrieval coefficients, quantified uncertainty, and more detailed information in the new harmonized format of the GT_ATS_2P product will allow for more significant exploitation of the historical LST data record from the ATSRs and a valuable near-real-time service from the Sea and Land Surface Temperature Radiometers (SLSTRs).
Funding
This work is jointly funded by the European Space Agency within the framework of the GlobTemperature project under the Data User Element of ESA's Fourth Earth Observation Envelope Programme (2013–2017) and a NERC grant to the National Centre for Earth Observation (NCEO) in the UK. This work utilizes AATSR data acquired from the Natural Environment Research Council Earth Observation Data Centre, profile data from the European Centre for Medium-range Weather Forecasts, land cover data from the Globcover Data User Element project, and fractional vegetation cover data from the European Commission funded Copernicus Global Land Service. SEVIRI LSTs were provided by the Land Surface Analysis Satellite Applications Facility (LSA SAF), a project funded by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), and in situ LST for the validation stations by Karlsruhe Institute of Technology (KIT). The authors would like to thank past and present colleagues at the University of Leicester, who have helped with the generation of plots and statistics: Olof Zeller, Tim Trent, and Michael Perry. Finally, we wish to express our gratitude to the reviewers of this paper. All data are freely accessible from the GlobTemperature Data Portal (http://data.globtemperature.info/).
History
Citation
Journal of Geophysical Research: Atmospheres, 2017, 122, 12,167–12,193
Author affiliation
/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Physics and Astronomy