DOI QR코드

DOI QR Code

Evaluation of Climatological Mean Surface Winds over Korean Waters Simulated by CORDEX-EA Regional Climate Models

CORDEX-EA 지역기후모형이 모사한 한반도 주변해 기후평균 표층 바람 평가

Choi, Wonkeun;Shin, Ho-Jeong;Jang, Chan Joo
최원근;신호정;장찬주

  • Received : 2018.11.13
  • Accepted : 2019.04.16
  • Published : 2019.06.30

Abstract

Surface winds over the ocean influence not only the climate change through air-sea interactions but the coastal erosion through the changes in wave height and direction. Thus, demands on a reliable projection of future changes in surface winds have been increasing in various fields. For the future projections, climate models have been widely used and, as a priori, their simulations of surface wind are required to be evaluated. In this study, we evaluate the climatological mean surface winds over the Korean Waters simulated by five regional climate models participating in Coordinated Regional Climate Downscaling Experiment (CORDEX) for East Asia (EA), an international regional climate model inter-comparison project. Compared with the ERA-interim reanalysis data, the CORDEX-EA models, except for HadGEM3-RA, produce stronger wind both in summer and winter. The HadGEM3-RA underestimates the wind speed and inadequately simulate the spatial distribution especially in summer. This summer wind error appears to be coincident with mean sea-level pressure in the North Pacific. For wind direction, all of the CORDEX-EA models simulate the well-known seasonal reversal of surface wind similar to the ERA-interim. Our results suggest that especially in summer, large-scale atmospheric circulation, downscaled by regional models with spectral nudging, significantly affect the regional surface wind on its pattern and strength.

Keywords

Surface wind;regional climate;dynamical downscaling;multi-model ensemble;Korean Waters

References

  1. Berrisford, P., and Coauthors, 2011: The ERA-interim archive, version 2.0. ERA Report Series 1, 23 pp.
  2. Cha, D.-H., and D.-K. Lee, 2009: Reduction of systematic errors in regional climate simulations of the summer monsoon over East Asia and the western North Pacific by applying the spectral nudging technique. J. Geophys. Res., 114, D14108, doi:10.1029/2008JD011176. https://doi.org/10.1029/2008JD011176
  3. Davies, T., M. J. P. Cullen, A. J. Malcolm, M. H. Mawson, A. Staniforth, A. A. White, and N. Wood, 2005: A new dynamical core for the Met Office's global and regional modelling of the atmosphere. Quart. J. Roy. Meteor. Soc., 131, 1759-1782. https://doi.org/10.1256/qj.04.101
  4. Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quart. J. R. Meteor. Soc., 137, 553-597, doi:10.1002/qj.828. https://doi.org/10.1002/qj.828
  5. Fitch, D. T., and J. K. Moore, 2007: Wind speed influence on phytoplankton bloom dynamics in the Southern Ocean Marginal Ice Zone. J. Geophys. Res., 112, C08006.
  6. Flato, G., and Coauthors, 2014: Evaluation of climate models. In T. F. Stocker et al. Eds., Climate Change 2013: the physical science basis. Cambridge University Press, 810-815.
  7. Giorgi, F., C. Jones, and G. R. Asrar, 2009: Addressing climate information needs at the regional level: the CORDEX framework, WMO Bull., 58, 175-183.
  8. Giorgi, F., and Coauthors, 2012: RegCM4: model description and preliminary tests over multiple CORDEX domains. Clim. Res., 52, 7-29, doi:10.3354/cr01018. https://doi.org/10.3354/cr01018
  9. Gormus, K. S., S. H. Kutoglu, D. Z. Seker, I. H. Ozolcer, M. Oruc, and B. Aksoy, 2014: Temporal analysis of coastal erosion in Turkey: a case study Karasu coastal region. J. Coast. Conserv., 18, 399-414, doi:10.1007/s11852-014-0325-0. https://doi.org/10.1007/s11852-014-0325-0
  10. Heo, K.-Y., T. Ha, J.-Y. Choi, K.-S. Park, J.-I. Kwon, and K. Jun, 2017: Evaluation of Wind and Wave Simulations using Different Global Reanalyses. J. Coastal Res., 79, 99-103, doi:10.2112/SI79-021.1. https://doi.org/10.2112/SI79-021.1
  11. Hong, S.-Y., and Coauthors, 2013: The global/regional integrated model system (GRIMs). Asia-Pac. J. Atmos. Sci., 49, 219-243, doi:10.1007/s13143-013-0023-0. https://doi.org/10.1007/s13143-013-0023-0
  12. Huang, B., S. Polanski, and U. Cubasch, 2015: Assessment of precipitation climatology in an ensemble of CORDEX-East Asia regional climate simulations. Clim. Res., 64, 141-158, doi:10.3354/cr01302. https://doi.org/10.3354/cr01302
  13. Im, E.-S., E.-H. Park, W.-T. Kwon, and F. Giorgi, 2006: Present climate simulation over Korea with a regional climate model using a one-way double-nested system. Theor. Appl. Climatol., 86, 187-200. https://doi.org/10.1007/s00704-005-0215-3
  14. Jang, C. J., H.-J. Shin, H. Jung, and C.-H. Kim, 2017: A preliminary Result on the Projection of Sea Surface Temperature in Korean Waters by Regional Climate Coupled Modelling. Journal of Coastal Disaster Prevention, 4, 35-41 (in Korean with English abstract). https://doi.org/10.20481/kscdp.2017.4.1.35
  15. Jang, C. J., W. Choi, H.-J. Shin, and C.-H. Kim, 2018: Future Changes in the Sea Surface Wind over the East Asian Marginal Seas Projected by Regional Climate Models. Journal of Coastal Research, 85, 591-595, doi:10.2112/SI85-119.1. https://doi.org/10.2112/SI85-119.1
  16. Kalognomou, E.-A., and Coauthors, 2013: A diagnostic evaluation of precipitation in CORDEX models over southern Africa. J. Climate, 26, 9477-9506, doi:10.1175/JCLI-D-12-00703.1. https://doi.org/10.1175/JCLI-D-12-00703.1
  17. Kanamaru, H., and M. Kanamitsu, 2007: Scale-selective bias correction in a downscaling of global analysis using a regional model. Mon. Wea. Rev., 135, 334-350. https://doi.org/10.1175/MWR3294.1
  18. Kang, H.-S., D.-H. Cha, and D.-K. Lee, 2005: Evaluation of the mesoscale model/land surface model (MM5/LSM) coupled model for East Asian summer monsoon simulations. J. Geophys. Res., 110, D10105. https://doi.org/10.1029/2004JD005266
  19. Kim, J., and Coauthors, 2014: Evaluation of the CORDEX-Africa multi-RCM hindcast: systematic model errors. Clim. Dyn., 42, 1189-1202, doi:10.1007/s00382-013-1751-7. https://doi.org/10.1007/s00382-013-1751-7
  20. Lee, D., C. Park, Y.-H. Kim, and S.-K. Min, 2016: Evaluation of the COSMO-CLM for East Asia Climate simulations: Sensitivity to Spectral Nudging. Journal of Climate Research, 11, 69-85, doi:10.14383/cri.2016.11.1.69 (in Korean with English abstract). https://doi.org/10.14383/cri.2016.11.1.69
  21. Lee, J.-W., S.-Y. Hong, E.-C. Chang, M.-S. Suh, and H.-S. Kang, 2014: Assessment of future climate change over East Asia due to the RCP scenarios downscaled by GRIMs-RMP. Clim. Dyn., 42, 733-747, doi:10.1007/s00382-013-1841-6. https://doi.org/10.1007/s00382-013-1841-6
  22. Lee, Y.-H., D.-H. Cha, and D.-K. Lee, 2008: Impact of horizontal resolution of regional climate model on precipitation simulation over the Korean Peninsula. Atmosphere, 18, 387-395 (in Korean with English abstract).
  23. Miguez-Macho, G., G. L. Stenchikov, and A. Robock, 2005: Regional climate simulations over North America: interaction of local processes with improved large-scale flow. J. Climate, 18, 1227-1246. https://doi.org/10.1175/JCLI3369.1
  24. Nikulin, G., and Coauthors, 2012: Precipitation climatology in an ensemble of CORDEX-Africa regional climate simulations. J. Climate, 25, 6057-6078, doi:10.1175/JCLI-D-11-00375.1. https://doi.org/10.1175/JCLI-D-11-00375.1
  25. Nonaka, M., and S.-P. Xie, 2003: Covariations of sea surface temperature and wind over the Kuroshio and its extension: Evidence for ocean-to-atmosphere feedback. J. Climate, 16, 1404-1413. https://doi.org/10.1175/1520-0442(2003)16<1404:COSSTA>2.0.CO;2
  26. Seo, J.-W., and Y.-S. Chang, 2003: Characteristics of the monthly mean sea surface winds and wind waves near the Korean Marginal Seas in the 2002 year computed using MM5/KMA and WAVEWATCH-III model. J. Korean Soc. Oceanography, 8, 262-273 (in Korean with English abstract).
  27. Simmons, A., S. Uppala, D. Dee, and S. Kobayashi, 2006: ERA-interim: New ECMWF reanalysis products from 1989 onwards. ECMWF Newsletter, 110, 25-35.
  28. Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang, and J. G. Powers, 2005: A description of the advanced research WRF version 2. NCAR Technical note NCAR/TN-4681STR, 88 pp.
  29. Swart, N. C., and J. C. Fyfe, 2012: Ocean carbon uptake and storage influenced by wind bias in global climate models. Nat. Clim. Change, 2, 47-52, doi:10.1038/nclimate1289. https://doi.org/10.1038/nclimate1289
  30. Uppala, S. M., D. Dee, S. Kobayashi, P. Berrisford, and A. Simmons, 2008: Towards a climate data assimilation system: status update of ERA-interim. ECMWF Newsletter, 115, 12-18.
  31. von Storch, H., H. Langerberg, and F. Feser, 2000: A spectral nudging technique for dynamical downscaling purposes. Mon. Wea. Rev., 128, 3664-3673. https://doi.org/10.1175/1520-0493(2000)128<3664:ASNTFD>2.0.CO;2

Acknowledgement

Grant : 북서태평양 순환과 기후 변동성이 한반도 주변해역 변화와 물질순환에 미치는 영향 I - 제주난류 변동성과 역할, 해양 수치모델링과 지능정보기술을 활용한 해양예측 정확도 향상 연구, 북서태평양 기후변화 예측 및 응용 연구

Supported by : 한국해양과학기술원, 해양수산과학기술진흥원, 한중해양과학공동연구센터