报告人：Dr. Darren Ghent, PI on the ESA LST CCI Project. Department of Physics and Astronomy, University of Leicester, UK
报告内容简介：Land surface temperature (LST) is the radiative skin temperature of the land and is derived from solar radiation. Instruments onboard Earth Observation satellites determine LST from top-of-atmosphere (TOA) radiances at microwave and thermal infrared wavelengths by applying a radiative transfer equation. This combines the upwelling radiance emitted by the ground, the upwelling radiance emitted by the atmosphere, and the down-welling radiance emitted by the atmosphere and reflected by the ground.
LST retrieval accuracy can be challenging as a result of emissivity variability and atmospheric effects. Surface emissivities can be highly variable owing to the heterogeneity of the land; a problem which is amplified in regions of high topographic variance or for larger viewing angles. Atmospheric effects caused by the presence of aerosols and by water vapour absorption can give a bias to the underlying LST. If not accounted for, atmospheric effects and emissivity variability can result in retrieval errors of several degrees.
报告人简介：Dr. Darren Ghent has over 10 years of experience working with land surface temperature data, from its retrieval to its exploitation. Indeed, his research interests include the interactions between the land-surface and the atmosphere in terms of the surface energy balance, carbon and water cycles. He is particularly concerned with validating land-surface temperature, both the products from Earth Observation and the simulations of land-surface models; developing improved land surface temperature algorithms, in particular being responsible for the algorithms for ESA instruments - AATSR and SLSTR; exploitation of land surface temperature in scientific and commercial applications; modelling the biogeochemical processes of terrestrial ecosystems; and climate feedbacks on various spatial and temporal scales. To improve the modelling of these processes, he has been involved in constraining land-surface.
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