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Changes in Climate Classification and Extreme Climate Indices from a High-Resolution Future Projection in Korea

  • Yun, Kyung-Sook (Division of Earth Environmental System, College of Natural Science, Pusan National University) ;
  • Heo, Ki-Young (Division of Earth Environmental System, College of Natural Science, Pusan National University) ;
  • Chu, Jung-Eun (Division of Earth Environmental System, College of Natural Science, Pusan National University) ;
  • Ha, Kyung-Ja (Division of Earth Environmental System, College of Natural Science, Pusan National University) ;
  • Lee, Eun-Jeong (Division of Earth Environmental System, College of Natural Science, Pusan National University) ;
  • Choi, Yumi (Division of Earth Environmental System, College of Natural Science, Pusan National University) ;
  • Kitoh, Akio (Meteorological Research Institute)
  • Published : 2012.08.31

Abstract

We investigate the future changes in the climate zone and six extreme temperature indices in Korea, using the 20-km highresolution atmospheric general circulation model (MRI-AGCM3.1S). The Trewartha and K$\ddot{o}$ppen climate classification schemes are applied, and four summer-based extreme temperature indices (i.e., summer days, tropical nights, growing degree days, and cooling degree days (CDD) and two winter-based indices (frost days and heating degree days (HDD) are analyzed. To represent significantly the change in threshold indices, the monthly mean bias is corrected in model. The model result reasonably captures the temporal and spatial distribution of the present-day extreme temperatures associated with topography. It was found that in the future climate, the area of the subtropical climate zone in Korea expands northward and increases by 21% under the Trewartha classification scheme and by 35% under the K$\ddot{o}$ppen classification scheme. The spatial change in extreme climate indices is significantly modulated by geographical characteristics in relation to land-ocean thermal inertia and topographical effects. The change is manifested more in coastal regions than in inland regions, except for that in summer days and HDD. Regions with higher indices in the present climate tend to reveal a larger increase in the future climate. The summer-based indices display an increasing trend, while the winter-based indices show a decreasing trend. The most significant increase is in tropical nights (+452%), whereas the most significant decrease is in HDD (-25%). As an important indicator of energy-saving applications, the changes in HDD and CDD are compared in terms of the frequency and intensity. The future changes in CDD reveal a higher frequency but a lower temperature than those in HDD. The more frequent changes in CDD may be due to a higher and less dispersed occurrence probability of extreme temperatures during the warm season. The greater increase in extreme temperature events during the summer season remains an important implication of projecting future changes in extreme climate events.

Keywords

References

  1. Alexander, L. V., and J. M. Arblaster, 2008: Assessing trends in observed and modelled climate extremes over Australia in relation to future projections. Int. J. Climatol., 29, 417-435.
  2. Alexander, L. V., and Coauthors, 2006: Global observed changes in daily climate extremes of temperature and precipitation. J. Geophy. Res., 111, D05109, doi:10.1029/2005JD006290.
  3. Bonsal, B. R., X. Zhang, L. A. Vincent, and W. D. Hogg, 2001: Characteristics of daily and extreme temperatures over Canada. J. Climate, 14, 1959-1976. https://doi.org/10.1175/1520-0442(2001)014<1959:CODAET>2.0.CO;2
  4. Boo, K.-O., W.-T. Kwon, and H.-J. Baek, 2006: Change of extreme events of temperature and precipitation over Korea using regional projection of future climate change. Geophy. Res. Lett., 33, L01701, doi:10.1029/ 2005GL023378.
  5. Buyukalaca, O., H. Bulut, and T. Yilmaz, 2001: Analysis of variable-base heating and cooling degree-days for Turkey. Applied Energy, 69, 269- 283. https://doi.org/10.1016/S0306-2619(01)00017-4
  6. Easterling, D. R., B. Horton, P. D. Jones, T. C. Peterson, T. R. Karl, and D. E. Parker, 1997: Maximum and minimum temperature trends for the globe. Science, 277, 364-367. https://doi.org/10.1126/science.277.5324.364
  7. Feng, L., T. Zhou, B. Wu, T. Li, and J.-J. Luo, 2011: Projection of future precipitation change over China with a high-resolution global atmospheric model. Adv. Atmos. Sci., 28(2), 464-476, doi: 10.1007/s00376- 010-1016-x.
  8. Gordon, R., and A. Bootsma, 1993: Analyses of growing degree-days for agriculture Atlantic Canada. Climate Res., 3, 169-176.
  9. Ha, K.-J., and K.-S. Yun, 2012: Climate change effects on tropical night days in Seoul, Korea. Theor. Appl. Climatol., 109, 191-203, doi:10.1007/s00704-011-0573-y.
  10. Ho, C.-H., and Coauthors, 2011: A projection of extreme climate events in the 21st century over East Asia using the community climate system model 3. Asia-Pacific J. Atmos. Sci., 47(4), 329-344.
  11. Im, E.-S., I.-W. Jung, and D.-H. Bae, 2011: The temporal and spatial structures of recent and future trends in extreme indices over Korea from a regional climate projection. Int. J. Climatol., 31, 72-86. https://doi.org/10.1002/joc.2063
  12. Jiang, F., X. Li, B. Wei, R. Hu, Z. Li, 2009: Observed trends of heating and cooling degree-days in Xinjiang Province, China. Theor. Appl. Climatol., 97, 349-360. https://doi.org/10.1007/s00704-008-0078-5
  13. Jung, I.-W., D.-H. Bae, and G. Kim, 2011: Recent trends of mean and extreme precipitation in Korea. Int. J. Climatol., 31, 359-370. https://doi.org/10.1002/joc.2068
  14. Karl, T. R., G. Kukla, V. N. Razuvayev, M. J. Changery, R. G. Quayle, R. R. Heim Jr., D. R. Easterling, and C. B. Fu, 1991: Global warming: Evidence for asymmetric diurnal temperature change. Geophys. Res. Lett. 18, 2253-2256. https://doi.org/10.1029/91GL02900
  15. Kharin, V. V., F. Zwiers, X. Zhang, and G. C. Hegerl, 2007: Changes in temperature and precipitation extremes in the IPCC Ensemble of Global Coupled Model Simulations. J. Climate, 20, 1419-1444. https://doi.org/10.1175/JCLI4066.1
  16. Kiktev, D., J. Caesar, L. V. Alexander, H. Shiogama, and M. Collier, 2007: Comparison of observed and multimodeled trends in annual extremes of temperature and precipitation. Geophy. Res. Lett., 34, L10702, doi: 10.1029/2007GL029539.
  17. Kim, J.-H., and J. I. Yun, 2008: On mapping growing degree-days (GDD) from monthly digital climate surfaces for South Korea, Korean J. of Agri. and Fore. Meteorol., 10(1), 1-8 (in Korean with English abstract). https://doi.org/10.5532/KJAFM.2008.10.1.001
  18. Kitoh, A., and S. Kusunoki, 2008: East Asian summer simulation by a 20- km mesh AGCM. Climate Dyn., 31, 389-401. https://doi.org/10.1007/s00382-007-0285-2
  19. Koppen, W. P., 1918: Klassification der Klimate nach Temperatur, Niederschlag und Jahreslauf. Petermanns Geogr. Mitt., 64, 193-203.
  20. Kwon, Y.-A., W.-T. Kwon, K.-O. Boo, Y. Choi., 2007: Future Projections on Subtropical Climate Regions over South Korea Using SRES A1B Data. Journal of the Korean Geographical Society, 42(3), 355-367 (in Korean with English abstract).
  21. Lee, S., and I. Heo, 2011: The impacts of urbanization on changes of extreme events of air temperature in South Korea. J. of Korean Geog. Soc., 46(3), 257-276 (in Korean with English abstract).
  22. Li, H., L. Feng, and T. Zhou, 2011a: Multi-model Projection of July- August Climate Extreme Changes over China under CO2 Doubling. Part I: Precipitation, Adv. Atmos. Sci., 28(2), 433-447,doi:10.1007/s00376-010-0013-4.
  23. Li, H., L. Feng, and T. Zhou, 2011b: Multi-model Projection of July- August Climate Extreme Changes over China under CO2 Doubling. Part II: Temperature, Adv. Atmos. Sci., 28(2), 448-463,doi:10.1007/s00376-010-0052-x.
  24. Li, H., T. Zhou, and J.-C. Nam, 2009: Comparison of daily extreme temperatures over eastern China and South Korea between 1996-2005. Adv. Atmos. Sci., 26(2), 253-264, doi:10.1007/s00376-009-0253-3.
  25. Meehl, G. A., and Coauthors, 2000: An introduction to trends in extreme weather and climate events: Observations, socioeconomic impacts, terrestrial ecological impacts, and model projection: Bull. Amer. Meteor. Soc., 81, 413-416. https://doi.org/10.1175/1520-0477(2000)081<0413:AITTIE>2.3.CO;2
  26. Mizuta, R., Y. Adachi, S. Yukimoto, S. Kusunoki, 2008: Estimation of future distribution of sea surface temperature and sea ice using CMIP3 multi-model ensemble mean. Technical Report of Meteorological Research Institute, 56, 28 pp.
  27. Rolim, G. S., M. B. P. Camargo, D. G. Lania, and J. F. L. Moraes, 2007: Climatic classification of Köppen and Thornthwaite sistems and their applicability in the determination of agroclimatic zonning for the state of Sao Paulo, Brazil. Bragantia, 66(4), 711-720.
  28. Trenberth, K.E., and Coauthors, 2007: Observations: surface and atmospheric climate change. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Solomon, S., and Coauthors, Eds., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
  29. Trewartha, G. T., 1968: An Introduction to weather and Climate. 4th edition, McGraw-Hill, New York, 408 pp.
  30. Yun, K.-S., S.-H. Shin, K.-J. Ha, A. Kitoh, and S. Kusunoki, 2008: East Asian Precipitation Change in the Global Warming Climate simulated by a 20-km mesh AGCM. Asia-Pacific J. Atmos. Sci., 44(3), 233-247.
  31. Zhai, P., X. Zhang, H. Wan, and X. Pan, 2005: Trends in total precipitation and frequency of daily precipitation extremes over China. J. Climate, 18, 1096-1108. https://doi.org/10.1175/JCLI-3318.1

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