A WRF Modeling Study on the Effects of Land Use Changes on Fog Off the West Coast of the Korean Peninsula

  • Chang Ki KimEmail author
  • Seong Soo Yum
  • Hyun-Goo Kim
  • Yong-Heack Kang


This study investigates, for the purpose of fog forecasting, the impacts of topography and land use changes on the characteristics of turbulence that directly contribute to the formation and dissipation of fog off the west coast of the Korean Peninsula using the Weather Research and Forecasting model version 3.5.1. During the investigation period, there are 59 coastal ground fog and 29 sea fog events. Local meteorological characteristics of coastal ground fog were similar to those of radiation fog typically seen over the land surface since the reclaimed island was constructed. After the sun rises, relative humidity over the land surface decreases rapidly—within a couple of hours—due to surface heating, which is controlled directly by shortwave radiation. Over the sea surface, however, the sea fog remains, with the relative humidity higher than 95% even during the daytime. For two selected cases, topography and land use were modified to identify turbulence characteristics through numerical modeling. This modification contributed to better forecasting the formation and dissipation of fog by changing characteristics of sensible and latent heat flux in the land surface model and then planetary boundary layer over the reclaimed island.


Topography land use weather research and forecasting model turbulence coastal ground fog sea fog 



This work was conducted under framework of the research and development program of the Korea Institute of Energy Research (B9-2414).


  1. Ballard, S. P., Golding, B. W., & Smith, R. N. B. (1991). Mesoscale model experimental forecasts of the Haar of northeast Scotland. Monthly Weather Review, 119, 2107–2123.CrossRefGoogle Scholar
  2. Brown, R., & Roach, W. T. (1976). The physics of radiation fog: II—a numerical study. Quarterly Journal of the Royal Meteorological Society, 102, 335–354.Google Scholar
  3. Chen, F., & Dudhia, J. (2001). Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Monthly Weather Reviews, 129, 569–585.CrossRefGoogle Scholar
  4. Dickinson, R. E., & Kennedy, P. (1992). Impacts on regional climate of Amazon deforestation. Geophysical Research Letters, 19, 1947–1950.CrossRefGoogle Scholar
  5. Ellrod, G. P. (1995). Advances in the detection and analysis of fog at night using GOES multispectral infrared imagery. Weather and Forecasting, 10, 606–619.CrossRefGoogle Scholar
  6. Fu, G., Guo, J. T., Xie, S. P., Duane, Y. H., & Zhang, M. G. (2006). Analysis and high-resolution modeling of a dense sea fog event over the Yellow Sea. Atmospheric Research, 81, 293–303.CrossRefGoogle Scholar
  7. Fu, G., Zhang, M., Duan, Y., Zhang, T., & Wang, J. (2004). Characteristics of sea fog over the Yellow Sea and the East China Sea. Kaiyo Monthly, 38, 99–107.Google Scholar
  8. Gao, S. H., Lin, H., Shen, B., & Fu, G. (2007). A heavy sea fog event over the Yellow Sea in March 2005: Analysis and numerical modeling. Advances in Atmospheric Sciences, 24, 65–81.CrossRefGoogle Scholar
  9. Gao, X., Luo, Y., Lin, W., Zhao, Z., & Giorgi, F. (2003). Simulation of effects of land use change on climate in China by a regional climate model. Advances in Atmospheric Sciences, 20, 583–592.CrossRefGoogle Scholar
  10. Gultepe, I., & Milbrandt, J. A. (2010). Probabilistic parameterizations of visibility using observations of rain precipitation rate, relative humidity, and visibility. Journal of Applied Meteorology and Climatology, 49, 36–46.CrossRefGoogle Scholar
  11. Hong, S. Y., Noh, Y., & Dudhia, J. (2006). A new vertical diffusion package with an explicit treatment of entrainment processes. Monthly Weather Reviews, 134, 2318–2341.CrossRefGoogle Scholar
  12. Kim, C. K., & Yum, S. S. (2010). Local meteorological and synoptic characteristics of fogs formed over Incheon international airport in the west coast of Korea. Advances in Atmospheric Sciences, 27, 761–776.CrossRefGoogle Scholar
  13. Kim, C. K., & Yum, S. S. (2012a). Marine boundary layer structure for the sea fog formation off the West Coast of the Korean Peninsula. Pure and Applied Geophysics, 169, 1121–1135.CrossRefGoogle Scholar
  14. Kim, C. K., & Yum, S. S. (2012b). A numerical study of sea-fog formation over cold sea surface using a one-dimensional turbulence model coupled with the weather research and forecasting model. Boundary-Layer Meteorology, 143, 481–505.CrossRefGoogle Scholar
  15. Kim, C. K., & Yum, S. S. (2013). A study on the transition mechanism of a stratus cloud into a warm sea fog using a single column model PAFOG coupled with WRF. Asia-Pacific Journal of Atmospheric Sciences, 49, 245–257.CrossRefGoogle Scholar
  16. Kim, C. K., & Yum, S. S. (2017a). Radiation in marine Fog. In D. Koračin & C. Dorman (Eds.), Marine Fog: Challenges and Advancements in Observations, Modeling, and Forecasting (p. 537). Cham: Springer.Google Scholar
  17. Kim, C. K., & Yum, S. S. (2017b). Turbulence in marine fog. In D. Koračin & C. Dorman (Eds.), Marine Fog: Challenges and Advancements in Observations, Modeling, and Forecasting (p. 537). Cham: Springer.Google Scholar
  18. Koracin, D., Businger, J., Dorman, C., & Lewis, J. (2005). Formation, evolution, and dissipation of coastal sea fog. Boundary-Layer Meteorology, 117, 447–478.CrossRefGoogle Scholar
  19. Kusaka, H., & Kimura, F. (2004). Thermal effects of urban canyon structure on the nocturnal heat island: Numerical experiment using a mesoscale model coupled with an urban canopy model. Journal of Applied Meteorology, 43, 1899–1910.CrossRefGoogle Scholar
  20. Leipper, D. F. (1995). Fog forecasting objectively in the California coastal area using LIBS. Weather Forecasting, 10, 741–762.CrossRefGoogle Scholar
  21. Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., & Clough, S. A. (1997). Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. Journal of Geophysical Research, 102, 16663–16682.CrossRefGoogle Scholar
  22. Paulson, C. A. (1970). The mathematical representation of wind speed and temperature profiles in the unstable atmospheric surface layer. Journal of Applied Meteorology, 9, 857–861.CrossRefGoogle Scholar
  23. Schreiner, A. J., Ackerman, S. A., Baum, B. A., & Heidinger, A. K. (2007). A multispectral technique for detecting low-level cloudiness near sunrise. Journal of Atmospheric Oceanic Technology, 24, 1800–1810.CrossRefGoogle Scholar
  24. Sorli, B., Pascal-Delannoy, F., Giani, A., Foucaran, A., & Boyer, A. (2002). Fast humidity sensor for high range 80–95% RH. Sensors and Actuators, A: Physical, 100, 24–31.CrossRefGoogle Scholar
  25. Stull, R. B. (1988). An Introduction to Boundary Layer Meteorology. Dordrecht: Kluwer Academic.CrossRefGoogle Scholar
  26. Thompson, G., Field, P. R., Rasmussen, R. M., & Hall, W. D. (2008). Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: Implementation of a New Snow Parameterization. Monthly Weather Reviews, 136, 5095–5115.CrossRefGoogle Scholar
  27. Thompson, G., Rasmussen, R. M., & Manning, K. (2004). Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis. Monthly Weather Reviews, 132, 519–542.CrossRefGoogle Scholar
  28. Turk, J., Vivekanandan, J., Lee, T., Durkee, P., & Nielsen, K. (1998). Derivation and applications of near-infrared cloud reflectances from GOES-8 and GOES-9. Journal of Applied Meteorology, 37, 819–831.CrossRefGoogle Scholar
  29. Wilks, D. S. (2011). Statistical Methods in the Atmospheric Sciences (3rd ed.). Cambridge: Academic Press.Google Scholar
  30. Zhang, J., Dong, W., Wu, L., Wei, J., Chen, P., & Lee, D.-K. (2005). Impact of land use changes on surface warming in China. Advances in Atmospheric Sciences, 22, 343–348.CrossRefGoogle Scholar
  31. Zhang, S.-P., Xie, S.-P., Liu, Q.-Y., Yang, Y.-Q., Wang, X.-G., & Ren, Z.-P. (2009). Seasonal variations of Yellow Sea Fog: Observations and mechanisms. Journal of Climate, 22, 6758–6772.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Chang Ki Kim
    • 1
    Email author
  • Seong Soo Yum
    • 2
  • Hyun-Goo Kim
    • 1
  • Yong-Heack Kang
    • 1
  1. 1.New and Renewable Energy Resource & Policy CenterKorea Institute of Energy ResearchDaejeonSouth Korea
  2. 2.Department of Atmospheric SciencesYonsei UniversitySeoulSouth Korea

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