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Development of numerical land surface temperature model of Jeju Island, South Korea based on finite element method

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Abstract

Owing to the importance of land-surface temperature (LST) and its variability in ecosystems, long-term LST monitoring is necessary. Because direct field measurements and satellite images have drawbacks, an appropriate LST simulation model is required. Therefore, in this study, we developed an hourly land-surface temperature model for Jeju Island and evaluated the variability in the predicted LST. The LST model was developed based on numerical analysis using the finite element method and calibrated and validated by comparing the simulated and measured temperature data obtained from four weather stations on Jeju Island. The simulated and measured LST have coefficients of determination of 0.96 and root mean square errors of 2.29 °C in validation. The model was used to predict LST data for a representative day of every month in 2018 using the mean monthly air temperature, and the variability of the data was calculated using the information entropy-based disorder index (DI). Linear relationships among the geographic coordinates, terrain attributes, mean LST, and DI were analyzed. Latitude and shaded relief were significantly linearly related with the overall mean LST and mean DI of the entire period, whereas longitude, elevation, and slope were not. The overall mean LST and mean DI for the entire period were negatively linearly related, but significant linear relationship did not appear in the case of individual months.

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Acknowledgements

This work was supported by a grant from the National Institute of Ecology (NIE), funded by the Ministry of Environment (MOE) of the Republic of Korea (NIE-B-2021-02). This work was also supported by the Creative-Pioneering Researchers Program through Seoul National University (SNU).

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Correspondence to Won Choi.

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Jeong, Yj., Lee, Si., Lee, Jh. et al. Development of numerical land surface temperature model of Jeju Island, South Korea based on finite element method. Environ Earth Sci 80, 357 (2021). https://doi.org/10.1007/s12665-021-09645-z

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  • DOI: https://doi.org/10.1007/s12665-021-09645-z

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