대기 (Atmosphere)

  • 제26권3호
  • /
  • Pages.373-386
  • /
  • 2016
  • /
  • 1598-3560(pISSN)
  • /
  • 2288-3266(eISSN)
한국기상학회 (Korean Meteorological Society)
권호 표지
DOI QR코드

DOI QR Code

지역 기후 앙상블 예측을 활용한 한반도 풍력 에너지의 시·공간적 변동성 연구

Variability of Wind Energy in Korea Using Regional Climate Model Ensemble Projection

  • 김유미 (공주대학교 대기과학과) ;
  • 김연희 (국립기상과학원 응용기상연구과) ;
  • 김나윤 (대전지방기상청 청주기상지청 기후서비스과) ;
  • 임윤진 (국립기상과학원 응용기상연구과) ;
  • 김백조 (국립기상과학원 응용기상연구과)
  • Kim, Yumi (Department of Atmospheric Sciences, Kongju National University) ;
  • Kim, Yeon-Hee (Applied Meteorology Research Division, National Institute of Meteorological Sciences) ;
  • Kim, Nayun (Applied Climate and Meteorological Service Division, Cheongju Branch Office of Meteorology) ;
  • Lim, Yoon-Jin (Applied Meteorology Research Division, National Institute of Meteorological Sciences) ;
  • Kim, Baek-Jo (Applied Meteorology Research Division, National Institute of Meteorological Sciences)
  • 투고 : 2016.03.31
  • 심사 : 2016.07.11
  • 발행 : 2016.09.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

The future variability of Wind Energy Density (WED) over the Korean Peninsula under RCP climate change scenario is projected using ensemble analysis. As for the projection of the future WED, changes between the historical period (1981~2005) and the future projection (2021~2050) are examined by analyzing annual and seasonal mean, and Coefficient of Variation (CV) of WED. The annual mean of WED in the future is expected to decrease compared to the past ones in RCP 4.5 and RCP 8.5 respectively. However, the CV is expected to increase in RCP 8.5. WEDs in spring and summer are expected to increase in both scenarios RCP 4.5 and RCP 8.5. In particular, it is predicted that the variation of CV for WED in winter is larger than other seasons. The time series of WED for three major wind farms in Korea exhibit a decrease trend over the future period (2021~2050) in Gochang for autumn, in Daegwanryeong for spring, and in Jeju for autumn. Through analyses of the relationship between changes in wind energy and pressure gradients, the fact that changes in pressure gradients would affect changes in WED is identified. Our results can be used as a background data for devising a plan to develop and operate wind farm over the Korean Peninsula.

키워드

참고문헌

  1. Ahn, J.-B., Y.-W. Choi, S. Jo, and J.-Y. Hong, 2014: Projection of 21st century climate over Korean Peninsula: temperature and precipitation simulated by WRFV3.4 based on RCP4.5 and 8.5 scenarios. Atmosphere, 24, 541-554 (in Korean with English abstract). https://doi.org/10.14191/Atmos.2014.24.4.541
  2. Barstad, I., A. Sorteberg, and M. S. Mesquita, 2012: Present and future offshore wind power potential in northern Europe based on downscaled global climate runs with adjusted SST and sea ice cover. Renew. Energy, 44, 398-405. https://doi.org/10.1016/j.renene.2012.02.008
  3. Brayshaw, D. J., A. Troccoli, R. Fordham, and J. Methven, 2011: The impact of large scale atmospheric circulation patterns on wind power generation and its potential predictability: A case study over the UK. Renew. Energy, 36, 2087-2096. https://doi.org/10.1016/j.renene.2011.01.025
  4. Byun, J.-Y., Y.-J. Choi, and B.-K. Seo, 2010: Characteristics of a wind map over the Korean Peninsula based on mesoscale model WRF. Atmosphere, 20, 195-210 (in Korean with English abstract).
  5. Byun, J.-Y., Y. Kim, and B.-C. Choi, 2014: Variability of future wind and solar resource over the Korean Peninsula based on climate change scenario. New. Renew. Energy, 10, 29-39 (in Korean with English abstract).
  6. Catter, T. R., M. Hulme, and M. Lal, 1999: IPCC-TG-CIA Guidelines on use of scenario data for climate impact and adaptation assessment Version 1. Task Group on Scenarios for impact Assessment, 69 pp.
  7. Cha, D.-H., and Coauthors, 2016: Future Changes in summer precipitation in regional climate simulations over the Korean Peninsula forced by multi-RCP scenarios of HadGEM2-AO. Asia-Pac. J. Atmos. Sci., 52, 139-149. https://doi.org/10.1007/s13143-016-0015-y
  8. Heo, C.-U., Y. Lee, and E.-J. Lee, 2010: Spatial distribution characteristics of wind map over Korea using meteorological resources. Atmosphere, 20, 61-71 (in Korean with English abstract).
  9. Hong, S.-Y., and Coauthors, 2013: The Global/Regional Integrated Model System (GRIMs). Asia-Pac. J. Atmos. Sci., 49, 210-243.
  10. Hong, S.-Y., and M. Kanamitsu, 2014: Dynamical downscaling: Fundamental issues from an NWP point of view and recommendations. Asia-Pac. J. Atmos. Sci., 50, 83-104. https://doi.org/10.1007/s13143-014-0029-2
  11. Hueging, H., R. Haas, K. Born, D. Jacob, and J. G. Pinto, 2013: Regional changes in wind energy potential over Europe using regional climate change model ensemble projections. J. Appl. Meteor. Climatol., 52, 903-917. https://doi.org/10.1175/JAMC-D-12-086.1
  12. Hwang, Y.-J., Y.-H. Kim, K.-Y. Chung, and D.-E. Chang, 2012: Predictability for heavy rainfall over the Korean Peninsula during the summer using TIGGE Model. Atmosphere, 22, 287-298 (in Korean with English abstract). https://doi.org/10.14191/Atmos.2012.22.3.287
  13. IEA, 2013: Tracking Clean Energy Progress 2013. International Energy Agency, 154 pp.
  14. Kim, D.-W., and H.-R. Byun, 2008: Spatial and temporal distribution of wind resources over Korea. Atmosphere, 18, 171-182 (in Korean with English abstract).
  15. Kim, D.-Y., J.-Y. Kim, and J.-J. Kim, 2013: Mesoscale simulations of multi-decadal variability in the wind resource over Korea. Asia-Pac. J. Atmos. Sci., 49, 183-192. https://doi.org/10.1007/s13143-013-0019-9
  16. Kim, H.-G., and Y.-H. Kang, 2012: The 2010 Wind resource map of the Korean Peninsula. J. Wind Eng. Inst. Korea, 16, 167-172.
  17. Kim, J.-Y., Y.-S. Ghim, and K.-Y. Chung, 2000: Analysis of wind data characteristics of automatic weather stations in Seoul and Inchon areas. Korean J. Atmos. Sci., 36, 153-166.
  18. Kim, J.-Y., D.-Y. Kim, and J.-H. Oh, 2014: Projected changes in wind speed over the Republic of Korea under A1B climate change scenario. Int. J. Climatol., 34, 1346-1356. https://doi.org/10.1002/joc.3739
  19. Kim, S., M.-K. Kim, J. Park, and D.-H. Jang, 2015: An analysis on the characteristics of the future upper wind over South Korea using climate change scenarios. J. Climate Res., 10, 273-285. https://doi.org/10.14383/cri.2015.10.3.273
  20. Kim, Y., Y.-J. Lim, H.-K. Lee, and B.-C. Choi, 2014: Spatio- temporal variability of future wind energy over the Korean Peninsula using climate change scenario. J. Korean Geogr. Soc., 49, 833-848.
  21. Korea Energy Agency, 2015: New & Renewable Energy Supply Statistics 2014 (2015 Edition). Korea Energy Agency, 135 pp (in Korean).
  22. Lee, J.-W., and S.-Y. Hong, 2014: Potential for added value to downscaled climate extremes over Korea by increased resolution of a regional climate model. Theor. Appl. Climatol., 117, 667-677. https://doi.org/10.1007/s00704-013-1034-6
  23. Lee, K., H.-J. Baek, S. Park, H.-S. Kang, and C.-H. Cho, 2012: Future projection of changes in extreme temperatures using high resolution regional climate change scenario in the Republic of Korea. J. Korean Geogr. Soc., 47, 208-225.
  24. Lu, J., G. A. Vecchi, and T. Reichler, 2007: Expansion of the Hadley cell under global warming. Geophys. Res. Lett., 34, L06805, doi:10.1029/2006GL028443.
  25. Mizuta, R., 2012: Intensification of extratropical cyclones associated with the polar jet change in the CMIP5 global warming projections. Geophys. Res. Lett., 39, doi:10.1029/2012GL053032.
  26. MOTIE, 2014: 2nd Korea Energy Master Plan. Ministry of Trade, Industry and Energy, 157 pp
  27. NIMR, 2011: Climate Change Report 2011. NIMR, 117 pp (in Korean).
  28. Outten, S. D., and I. Esau, 2013: Extreme winds over Europe in the ENSEMBLES regional climate models. Atmos. Chem. Phys., 13, 5163-5182. https://doi.org/10.5194/acp-13-5163-2013
  29. Pryor, S. C., and R. J. Barthelmie, 2005: Empirical downscaling of wind speed probability distributions. J. Geophys. Res., 110, D19109. https://doi.org/10.1029/2005JD005899
  30. Pryor, S. C., and J. T. Schoof, 2010: Importance of the SRES in projections of climate change impacts on near-surface wind regimes. Meteorol. Z., 19, 267-273. https://doi.org/10.1127/0941-2948/2010/0454
  31. Pryor, S. C., G. Nikulin, and C. Jones, 2012a: Influence of spatial resolution on regional climate model derived wind climates. J. Geophys. Res., 117, D03117, doi:10.1029/2011JD016822.
  32. Pryor, S. C., R. J. Barthelmie, N. E. Clausen, M. Drews, N. MacKeller, and E. Kjellstrom, 2012b: Analyses of possible changes in intense and extreme wind speeds over northern Europe under climate change scenarios. Clim. Dynam., 38, 189-208. https://doi.org/10.1007/s00382-010-0955-3
  33. Reyers, M., J. G. Pinto, and J. Moemken, 2015: Statisticaldynamical downscaling for wind energy potentials: Evaluation and applications to decadal hindcasts and climate change projections. Int. J. Climatol., 35, 229-244. https://doi.org/10.1002/joc.3975
  34. Suh, M.-S., S.-K. Oh, Y.-S. Lee, J.-B. Ahn, D.-H. Cha, D.-K. Lee, S.-Y. Hong, S.-K. Min, S.-C. Park, and H.-S. Kang, 2016: Projections of high resolution climate changes for South Korea using multiple-regional climate models based on four RCP scenarios. Part 1: surface air temperature. Asia-Pac. J. Atmos. Sci., 52, 151-169. https://doi.org/10.1007/s13143-016-0017-9
  35. Tobin, I., R. Vautard, I. Balog, F. M. Bréon, S. Jerez, P. M. Ruti, F. Thais, M. Vrac, and P. Yiou, 2015: Assessing climate change impacts on European wind energy from ENSEMBLES high-resolution climate projections. Climatic Change, 128, 99-112. https://doi.org/10.1007/s10584-014-1291-0
  36. Wanner, H., S. Bronnimann, C. Casty, D. Gyalistras, J. Luterbacher, C. Schmuts, D. B. Stephenson, and E. Xoplaki, 2001: North Atlantic Oscillation-concepts and studies. Surv. Geophys., 22, 321-381. https://doi.org/10.1023/A:1014217317898
  37. Zhang, D. F., X. J. Gao, L. C. Ouyang, and W. J. Dong, 2008: Simulation of present climate over East Asia by a regional climate model. J. Trop. Meteorol., 14, 19-23.
  38. Zoster, E., R. Buizza, and D. Richardson, 2009: "Jumpiness" of the ECMWF and Met Office EPS control and ensemble-mean forecasts. Mon. Wea. Rev., 137, 3823-3836. https://doi.org/10.1175/2009MWR2960.1