Augmented multiple regression algorithm for accurate estimation of localized solar irradiance

Ji Nyeong Choi, Sanghee Lee, Ki Beom Ahn, Sug Whan Kim, Jinho Kim

Research output: Contribution to journalArticlepeer-review


The seasonal variations in weather parameters can significantly affect the atmospheric transmission characteristics. Herein, we propose a novel augmented multiple regression algorithm for the accurate estimation of atmospheric transmittance and solar irradiance over highly localized areas. The algorithm employs 1) adaptive atmospheric model selection using measured meteorological data and 2) multiple linear regression computation augmented with the conventional application of MODerate resolution atmospheric TRANsmission (MODTRAN). In this study, the proposed algorithm was employed to estimate the solar irradiance over Taean coastal area using the 2018 clear days' meteorological data of the area, and the results were compared with the measurement data. The difference between the measured and computed solar irradiance significantly improved from 89.27 ± 48.08σ W/m2 (with standard MODTRAN) to 21.35 ± 16.54σ W/m2 (with augmented multiple regression algorithm). The novel method proposed herein can be a useful tool for the accurate estimation of solar irradiance and atmospheric transmission characteristics of highly localized areas with various weather conditions; it can also be used to correct remotely sensed atmospheric data of such areas.

Original languageEnglish
Pages (from-to)1435-1447
Number of pages13
JournalKorean Journal of Remote Sensing
Issue number6-11
Publication statusPublished - 2020

Bibliographical note

Publisher Copyright:
© 2020 Korean Society of Remote Sensing. All rights reserved.

All Science Journal Classification (ASJC) codes

  • Engineering (miscellaneous)
  • Computers in Earth Sciences
  • Earth and Planetary Sciences (miscellaneous)


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