DOI QR코드

DOI QR Code

Impact of High-Resolution Sea Surface Temperatures on the Simulated Wind Resources in the Southeastern Coast of the Korean Peninsula

고해상도 해수면온도자료가 한반도 남동해안 풍력자원 수치모의에 미치는 영향

  • Lee, Hwa-Woon (Department of Earth Environmental System, Pusan National University) ;
  • Cha, Yeong-Min (Department of Earth Environmental System, Pusan National University) ;
  • Lee, Soon-Hwan (Institute of Environmental Studies, Pusan National University) ;
  • Kim, Dong-Hyeok (Department of Earth Environmental System, Pusan National University)
  • 이화운 (부산대학교 지구환경시스템학부) ;
  • 차영민 (부산대학교 지구환경시스템학부) ;
  • 이순환 (부산대학교 환경문제연구소) ;
  • 김동혁 (부산대학교 지구환경시스템학부)
  • Received : 2009.09.25
  • Accepted : 2010.01.06
  • Published : 2010.02.28

Abstract

Accurate simulation of the meteorological field is very important to assess the wind resources. Some researchers showed that sea surface temperature (SST) plays a leading role on the local meterological simulation. New Generation Sea Surface Temperature (NGSST), Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA), and Real-Time Global Sea Surface Temperature (RTG SST) have different spatial distribution near the coast and OSTIA shows the best accuracy compared with buoy data in the southeastern coast of the Korean Peninsula. Those SST products are used to initialize the Weather Research and Forecasting (WRF) Model for November 13-23 2008. The simulation of OSTIA shows better result in comparison with NGSST and RTG SST. NGSST shows a large difference with OSTIA in horizontal and vertical wind fields during the weak synoptic condition, but wind power density shows a large difference during strong synoptic condition. RTG SST shows the similar patterns but smaller the magnitude and the extent.

Keywords

References

  1. 경남호, 윤정은, 장문석, 장동순, 2003, 한반도해역의 해상 풍력자원 평가, 한국태양에너지학회 논문집, 23(2), 35-41.
  2. 김현구, 2008, 남한 풍력자원 잠재량의 예비적 산정, 한국태양에너지학회 논문집, 28(6), 1-7.
  3. 김현구, 이화운, 정우식, 2005, 한반도 바람지도 구축에 관한 연구 I. 원격탐사자료를 이용한 해상풍력자원 평가, 한국대기환경학회지, 21(1), 63-72.
  4. 김현구, 최재우, 2002, 풍력에너지 이용 및 개발현황, RIST 연구논문, 16(4), 479-485.
  5. Burls, N., Reason, C. J. C., 2008, Modelling the sensitivity of coastal winds over the Southern Benguela upwelling system to different SST forcing, Journal of Marine Systems, 74(1-2), 561-584. https://doi.org/10.1016/j.jmarsys.2008.04.009
  6. Cho, Y. K., Kim, K., 2000, Branching Mechanism of the Tsushima Current in the Korea Strait, Journal of Physical Oceanography, 30(11), 2788-2797. https://doi.org/10.1175/1520-0485(2000)030<2788:BMOTTC>2.0.CO;2
  7. Donlon, C., Robinson, I., Casey, K. S., Vazquez- Cuervo, J., Armstrong, E., Arino, O., Gentemann, C., May, D., LeBorgne, P., Piolle, J., Barton, I., Beggs, H., Poulter, D. J. S., Merchant, C. J., Bingham, A., Heinz, S., Harris, A., Wick, G., Emery, B., Minnett, P., Evans, R., Llewellyn-Jones, D., Mutlow, C., Reynolds, R. W., Kawamura , H., Rayner, N., 2007, The Global Ocean Data Assimilation Experiment High-resolution Sea Surface Temperature Pilot Project, Bulletin of the American Meteorological Society, 88(8), 1197-1213. https://doi.org/10.1175/BAMS-88-8-1197
  8. Guan, L., Kawamura, H., 2004, Merging satellite infrared and microwave SSTs: methodology and evaluation of the new SST. Journal of Oceanography, 60(5), 905-912. https://doi.org/10.1007/s10872-005-5782-5
  9. Katoh, O., 1994, Structure of the Tsushima Current in the southwestern Japan Sea, Journal of Oceanography, 50(3), 317-338. https://doi.org/10.1007/BF02239520
  10. LaCasse, K. M., Splitt, M. E., Lazarus , S. M., Lapenta, W. M., 2008, Impact of High-Resolution Sea Surface Temperatures on the Simulated Nocturnal Florida Marine Boundary Layer, Monthly Weather Review, 136(4), 1349-1372. https://doi.org/10.1175/2007MWR2167.1
  11. Sakaida, F., Takahashi, S., Shimada, T., Kawai, Y., Kawamura, H., Hosoda, K., Guan, L., 2005, The production of the new generation sea surface temperature (NGSST-O Ver.1.0) in Tohoku University, Geoscience and Remote Sensing Symposium, 2005, IGARSS '05. Proceedings. 2005 IEEE International 4, 2602-2605. https://doi.org/10.1109/IGARSS.2005.1525518
  12. Sakurai, T., Yukio, K., Kuragano, T., 2005, Merged satellite and in-situ data global daily SST. geoscience and remote sensing symposium, 2005, IGARSS’5. Proceedings of the 2005 IEEE International, 4, 2606-2608.
  13. Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda, M. G., Huang, X. Y., Wang W., Powers, J. G., 2008, A description of the advanced research WRF version 3, NCAR/TN–-475+STR NCAR TECHNICAL NOTE, 125.
  14. Skyllingstad, E. D., Vickers, D., Mahrt, L., Samelson, R., 2007, Effects of mesoscale sea-surface temperature fronts on the marine atmospheric boundary layer, Boundary-Layer Meteorology, 123, 219-237. https://doi.org/10.1007/s10546-006-9127-8
  15. Stark, J. D., Donlon, C. J., O’arroll, A., 2008, Determination of AATSR Biases Using the OSTIA SST Analysis System and a Matchup Database, Journal of Atmospheric and Oceanic Technology, 25(7), 1208- 1217. https://doi.org/10.1175/2008JTECHO560.1
  16. Stark, J. D., Donlon, C. J., Martin, M. J., McCulloch, M. E., 2007, OSTIA : An operational, high resolution, real time, global sea surface temperature analysis system, OCEANS 2007 - Europe, 1-4.
  17. Thiebaux, J., Rogers, E., Wang, W., Katz, B., 2003, A new high-resolution blended real-time global sea surface temperature analysis, Bulletin of the American Meteorological Society, 84(5), 645-656. https://doi.org/10.1175/BAMS-84-5-645
  18. Xie, J., Zhu, J., Li, Y., 2008, Assessment and inter-comparison of five high-resolution sea surface temperature products in the shelf and coastal seas around China, Continental Shelf Research, 28(10-11), 1286-1293. https://doi.org/10.1016/j.csr.2008.02.020

Cited by

  1. A Study of the Effects of SST Deviations on Heavy Snowfall over the Yellow Sea vol.23, pp.2, 2013, https://doi.org/10.14191/Atmos.2013.23.2.161
  2. Study on the Characteristics of PM Distribution in Coastal and Inland Cities Correlation and Its Correlation vol.24, pp.11, 2015, https://doi.org/10.5322/JESI.2015.24.11.1513
  3. A Study on Effect of Improvement Plan for Wind Energy Forecasting vol.31, pp.1, 2015, https://doi.org/10.5572/KOSAE.2015.31.1.001