Abstract
The measurement of near-surface air temperature (Ta) is critically important for understanding the Earth’s energy and water circulation system and for diverse modelling applications. Ta data obtained from meteological ground stations are basically available but not suitable for large-scale areas, because of their spatial limitation. Remote-sensing techniques can provide a spatially well-distributed Ta map. However, the current remote-sensing methodology for Ta mapping has accuracy inferior to common expectations in terms of the region of various terrestrial ecosystems and climatic conditions. Our aim was to develop a midday Ta retrieval algorithm with reasonable accuracy over Northeast Asia during one seasonal year. In consideration of the various environmental conditions in our study area, Ta was calculated using land surface temperature and the normalized difference vegetation index in the nine cases derived from the combination of surface and atmospheric moisture conditions, and a weighting factor was applied to reduce the bias error among Ta results from nine cases. The reasonable pixel window size was established as 13 × 13. The validation process yielded a coefficient of determination (R2), root mean square error, and bias values of 0.9401, 2.8865 K, and 0.4920 K, respectively. Although the study area includes diverse land-cover and climatic conditions, our satellite-derived Ta data provided better results compared with a previous study of only four cases with no weighting function in the Korean peninsula. Our suggested methodology will be useful in estimating Ta using satellite data, particularly over complex land surfaces.
Published Version
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