Land Surface Temperature (LST) is closely linked to the surface energy balance encapsulating information on energy, water and carbon exchanges between the surface and the atmosphere. As such, LST has been recognized as an Essential Climate Variable and the exploitation of LST Climate Data Records has been steadily increasing over the last years. The EUMETSAT Satellite Applications Facility on Land Surface Analysis (LSA SAF) has released an LST Climate Data Record (CRD) generated from observations provided by Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board Meteosat Second Generation (MSG) satellites. The CDR consists of 15-minute level-2 LST derived using a Generalized Split Windows (GSW) algorithm covering the period 2004-2015 and updated in near real time ever since. The SEVIRI LST data are distributed together with an estimate of product uncertainty, which in turn is computed taking into account the algorithm uncertainty (dependent on retrieval conditions) and the propagation of input uncertainties into the final product. Here we show how those various components were determined. The validation results of LST against in situ measurements reveal that overall LST meets the expected accuracy requirements (target accuracy within 2K). The assessment of the LST product uncertainties suggests that these are generally in line with what would be expected. We found, however, desert regions presented an overestimation of LST uncertainties, which prompted a revision of emissivity and respective uncertainties over those areas.
Topic : Theme 1: Biosphere Monitoring.
Reference : T1-D1
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