Seasonal Variations of Direct Solar Irradiance with Ground and Air Atmospheric Data Fusion for Peninsular Type Coastal Area

지상 및 고도별 대기측정 자료 융합을 이용한 반도형 해안지역의 직달일사량 계절 변화 연구

  • Choi, Ji Nyeong (Department of Astronomy, Yonsei University) ;
  • Lee, Sanghee (Research Center for Atmospheric Environment, Hankuk University of Foreign Studies) ;
  • Seong, Sehyun (Department of Astronomy, Yonsei University) ;
  • Ahn, Ki-Beom (Department of Astronomy, Yonsei University) ;
  • Kim, Sug-Whan (Department of Astronomy, Yonsei University) ;
  • Kim, Jinho (The 5th R&D Institute, Agency for Defense Development) ;
  • Park, Sanghyun (The 5th R&D Institute, Agency for Defense Development) ;
  • Jang, Sukwon (The 5th R&D Institute, Agency for Defense Development)
  • 최지녕 (연세대학교 천문우주학과) ;
  • 이상희 (한국외국어대학교 대기환경연구센터) ;
  • 성세현 (연세대학교 천문우주학과) ;
  • 안기범 (연세대학교 천문우주학과) ;
  • 김석환 (연세대학교 천문우주학과) ;
  • 김진호 (국방과학연구소 제5기술연구본부) ;
  • 박상현 (국방과학연구소 제5기술연구본부) ;
  • 장석원 (국방과학연구소 제5기술연구본부)
  • Received : 2020.04.30
  • Accepted : 2020.05.25
  • Published : 2020.06.30


Localized solar irradiance is normally derived from atmospheric transmission influenced by atmospheric composition and conditions of the target area. Specially, for the area with complex coastal lines such as Taean gun, the accurate estimation of solar irradiance requires for in depth analysis of atmospheric transmission characteristics based on the localized vertical profiles of the key atmospheric parameters. Using MODTRAN (MODerate resolution atmospheric TRANsmission) 6, we report a computational study on clear day atmospheric transmission and direct solar irradiance estimation of Taean gun using the data collected from 3 ground stations and radiosonde measurement over 93 clear days in 2018. The MODTRAN estimated direct solar irradiance is compared with the measurement. The results show that the normalized residual mean (NRM) is 0.28 for the temperature based MODTRAN atmospheric model and 0.32 for the pressure based MODTRAN atmospheric model. These values are larger than 0.1~0.2 of the other study and we understand that such difference represents the local atmospheric characteristics of Taean gun. The results also show that NRM tends to increase noticeably in summer as the temperature increases. Such findings from this study can be very useful for estimation and prediction of the atmospheric condition of the local area with complex coastal lines.


  1. Berk, A., P. Conforti, and F. Hawes, 2015. An accelerated line-by-line option for MODTRAN combining on-the-fly generation of line center absorption within $0.1cm^{-1}$ bins and pre-computed line tails, Proc. of SPIE Defense + Security, Baltimore, MD, May 21, vol. 9472, p. 947217.
  2. Berk, A., P. Conforti, R. Kennett, T. Perkins, F. Hawes, and J. van den Bosch, 2014. MODTRAN6${(R)}$: a major upgrade of the MODTRAN${(R)}$ radiative transfer code, Proc. of 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Lausanne, Jun. 24-27, pp. 1-4.
  3. Cha, J.W., H.-J. Ko, B. Shin, H.-J. Lee, J.E. Kim, B. Ahn, and S.-B. Ryoo, 2016. Characteristics of Aerosol Mass Concentration and Chemical Composition of the Yellow and South Sea around the Korean Peninsula Using a Gisang 1 Research Vessel, Atmosphere, 26(3): 357-372 (in Korean with English abstract).
  4. Choi, Y., Y. Kim, M. Kim, M. Park, S. Min, Y.-A. Kwon, and M.-K. Kim, 2018. The Determination of Detailed Climate Classification and Future Projections in the Republic of Korea using Highresolution Grid Climate Data and Trewartha Climate Classification, Journal of Climate Research, 13(4): 247-261 (in Korean with English abstract).
  5. Driggers, R.G., J.M. Nichols, and M.H. Friedman, 2012. Introduction to Infrared and Electro-Optical Systems, 2nd edition, Artech House, Norwood, MA, USA.
  6. Gathman, S.G., 1983. Optical properties of the marine aerosol as predicted by the Navy aerosol model, Optical Engineering, 22(1): 220157.
  7. Halthore, R.N., S.E. Schwartz, J.J. Michalsky, G.P. Anderson, R.A. Ferrare, B.N. Holben, and H.M. Ten Brink, 1997. Comparison of model estimated and measured direct-normal solar irradiance, Journal of Geophysical Research: Atmospheres, 102(D25): 29991-30002.
  8. Han, K. and J. W. Hahn, 2018. Uncertainty analysis of the flame temperature determination based on atmospheric absorption effect with optical emission spectroscopy, Combustion Science and Technology, 190(11): 2044-2060.
  9. Hukseflux, Theremal Sensors, 2017. User Manual LP02: Second class pyranometer, Hukseflux, Delft, Netherlands.
  10. Korea Meteorological Administration, 2011. Climatological Normals of Korea 1981-2010, Korea Meteorological Administration, Seoul, Korea (in Korean).
  11. Jensen, D.R., C.H. Wash, and M.S. Jordan, 1998. Air mass parameterization and coastal aerosol modeling, Proc. of SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, San Diego, CA, Nov. 3, vol. 3433, pp. 2-9.
  12. Jo, D.-K. and Y.-H. Kang, 2006. A Detailed Survey of Normal Radiation and Clear-day for the Construction of Solar Concentrating System in Korea, Journal of the Korean Solar Energy Society, 26(3): 53-62 (in Korean with English abstract).
  13. Lee, K.-H., K.-T. Lee, J.-H. Kim, and G.-H. Mun, 2018. Characteristics of Aerosol Mass Concentrations and Size Distribution Measured at Anheung, Korea, Journal of Korean Society for Atmospheric Environment, 34(5): 677-686 (in Korean with English abstract).
  14. Liou, K.-N., 2002. An Introduction to Atmospheric Radiation, 2nd edition, Academic Press, San Diego, CA, USA.
  15. Lisenko, S.A., 2018. Atmospheric correction of multispectral satellite images based on the solar radiation transfer approximation model, Atmospheric and Oceanic Optics, 31(1): 72-85.
  16. Park, S.U., K.A. Koo, and W.-S. Kong, 2016. Potential Impact of Climate Change on Distribution of Warm Temperate Evergreen Broad-leaved Trees in the Korean Peninsula, Journal of the Korean Geographical Society, 51(2): 201-217 (in Korean with English abstract).
  17. Reda, I. and A. Andreas, 2004. Solar position algorithm for solar radiation applications, Solar Energy, 76(5): 577-589.
  18. Reno, M.J., C.W. Hansen, and J.S. Stein, 2012. Global horizontal irradiance clear sky models: Implementation and analysis, SANDIA report SAND2012-2389, U.S. Department of Commerce National Technical Information Service, Springfield, VA, USA.
  19. Reindl, D.T., W.A. Beckman, and J. A. Duffie, 1990. Diffuse fraction correlations, Solar Energy, 45(1): 1-7.
  20. Sengupta, M., Y. Xie, A. Lopez, A. Habte, G. Maclaurin, and J. Shelby, 2018. The national solar radiation data base (NSRDB), Renewable and Sustainable Energy Reviews, 89: 51-60.
  21. Stotts, L.B. and J. Schroeder, 2019. Atmospheric Modeling Using PcModWin${(c)}$/MODTRAN${(R)}$, SPIE Press, Bellingham, WA, USA.
  22. Thomassen, J., A.D. van Rheenen, E.B. Madsen, M. Pszczel, N. Bilton, and O. Pushkarov, 2018. Sensitivity of input parameters to modelling of atmospheric transmission of long-wave infrared radiation at sea under warm and humid conditions, Proc. of SPIE Security + Defence, Berlin, Oct. 9, vol. 10794, p. 107940A.
  23. Vaisala, 2002. User's Guide, Anemometer WAA151, M210293en-A, Vaisala, Helsinki, Finland.
  24. Vaisala, 2004. Present Weather Detector PWD22 User's Guide, M210543EN-B, Vaisala, Helsinki, Finland.
  25. Vaisala, 2018a. Radiosonde RS41-D, B211609EN-D, Vaisala, Helsinki, Finland.
  26. Vaisala, 2018b. Ceilometer CL31 for Cloud Height Detection, B210415EN-G, Vaisala, Helsinki, Finland.
  27. Vogelbacher, S., D. Sprung, A.M. van Eijk, and K. Stein, 2015. Influence of aerosols on atmospheric transmission at the Baltic Sea: comparison of experimental results with model simulations using MODTRAN, Proc. of SPIE Remote Sensing, Toulouse, Oct. 8, vol. 9641, p. 964106.