A Study on Predictability of Snowfall Amount due to Fine Difference of Spatial Distribution of Remote Sensing based Sea Surface Temperature

원격 탐사 기반 해양 표면 온도의 미세 분포 차이에 따른 강설량 예측성 연구

  • Lee, Soon-Hwan (Department of Earth Science Education, Pusan National University) ;
  • Yoo, Jung-Woo (Division of Earth Environment System, Pusan National University)
  • 이순환 (부산대학교 지구과학교육과) ;
  • 유정우 (부산대학교 지구환경시스템학부)
  • Received : 2014.05.26
  • Accepted : 2014.08.14
  • Published : 2014.08.29


In order to understand the relation between the distribution of sea surface temperature and heavy snowfall over western coast of the Korean peninsula, several numerical assessments were carried out. Numerical model used in this study is WRF, and sea surface temperature data were FNL(National Center for Environment Prediction-Final operational global analysis), RTG(Real Time Global analysis), and OSTIA(Operational Sea Surface Temperature and Sea Ice Analysis). There were produced on the basis of remote sensing data, such as a variety of satellite and in situ observation. The analysis focused on the heavy snowfall over Honam districts for 2 days from 29 December 2010. In comparison with RTG and OSTIA SST data, sensible and latent heat fluexes estimated by numerical simulation with FNL data were higher than those with RTG and OSTIA SST data, due to higher sea surface temperature of FNL. General distribution of RTG and OSTIA SST showed similar, however, fine spatial differences appear in near western coast of the peninsula. Estimated snow fall amount with OSTIA SST was occurred far from the western coast because of higher SST over sea far from coast than that near coast. On the other hand, snowfall amount near coast is larger than that over distance sea in simulation with RTG SST. The difference of snowfall amount between numerical assessment with RTG and OSTIA is induced from the fine difference of SST spatial distributions over the Yellow sea. So, the prediction accuracy of snowfall amount is strongly associated with the SST distribution not only over near coast but also over far from the western coast of the Korean peninsula.


Supported by : 부산대학교


  1. Ahn, J. B., Cho, E. H., 1998, Atmospheric mesoscale model responses to given Sea-Surface Temperature around Korean Peninsula, Korean Journal of the Atmospheric Sciences, 34(4), 643-651.
  2. Cha, Y. M., Lee, H. W., Lee, S. H., 2011, Impacts of the high-resolution sea surface temperature distribution on modeled snowfall formation over the Yellow Sea during a cold-air outbreak. Weather and Forecasting, 26, 487-503.
  3. Jhun, J. G., Lee, D. K., Lee, H. A., 1994, A study on the heavy snowfalls occurred in South Korea, Korean Journal of the Atmospheric Sciences, 30(1), 97-117.
  4. Cheong, S. H., Byun, K. Y., Lee, T. Y., 2006, Classification of snowfalls over the Korean Peninsula based on developing mechanism, Atmosphere, 16, 33-48.
  5. Jeong, J. I., Park, R. J., 2013, A study of the effects of SST deviations on heavy snowfall over the Yellow Sea, Atmosphere, 23(2), 161-169.
  6. Jeong, Y. K., 1999, Synoptic environment associated with the heavy snowfall in the southwestern region of Korean peninsula, Journal of Korean Earth Science Society, 20(4), 398-410.
  7. Kang, S. D., Ahn, J. B., 2008, Numerical study on the formation and maintenance mechanisms of cloud street in the East Sea during cold air outbreak. Asia-Pacific Journal of Atmospheric Science, 44, 105-119.
  8. Lee, K. M., Lee, S. H., 2006, The spatial distribution of snowfall and its development mechanism over the Honam area, Journal of Korean Geographical Society, 41(4), 457-469.
  9. Lee, S. H., Chun, J. H., 2003, The distribution of snowfall by Siberian High in the Honam region - Emphasized on the westward region of the Noryung mountain ranges, Journal of Korean Geographical Society, 38(2), 173-183.
  10. Lee, S. H., Ryu, C. R., 2010, Influence of continuous satellite-based SST distribution on heavy snowfall events over the Korean Peninsula. International Journal of Remote Sensing, 31, 2853-2883.
  11. Park, R. S., Cho, Y. K., Choi, B. J., Song, C. H., 2011, Implications of Sea Surface Temperature deviations in the prediction of wind and precipitable water over the Yellow Sea. Journal of Geophysical Research, 116, D17106.
  12. Skamarock, W. C., Coauthors, 2008, A description of the advanced research WRF version 3. NCAR Tech. Note NCAR/TN-4751STR, 113pp.
  13. Stark, J. D., Donlon, C.D., O'Carrol, A., 2008, Determination of AATSR Biases using OSTIA SST Analysis system and a match up database, Journal of atmospheric and oceanic Technology, 25(7), 1208-1217.
  14. Thiebaux, J., Rogers, E., Wang, W., Katz, B., 2003, A new high-resolution blended real-time global sea surface temperature analysis, Bulletins of the American Meteorological Society, 84(5), 645-656.
  15. Yamamoto, M., 2012, Mesoscale structures of two types of cold-air outbreaks over the East China Sea and the effect of coastal Sea Surface Temperature, Meteorology and Atmospheric Physics, 115, 89-112.