DOI QR코드

DOI QR Code

Effect of Aerosol Feedback on Solar Radiation in the Korean Peninsula Using WRF-CMAQ Two-way Coupled Model

WRF-CMAQ 결합모델을 이용한 에어로졸 피드백 효과가 한반도 일사량에 미치는 영향 연구

  • Yoo, Jung-Woo (Division of Earth Environmental System, Pusan National University) ;
  • Park, Soon-Young (Institute of Environment Studies, Pusan National University) ;
  • Jeon, WonBae (Institute of Environment Studies, Pusan National University) ;
  • Kim, Dong-Hyeok (Seohaean Research Institute, ChungNam Institute) ;
  • Lee, HwaWoon (Division of Earth Environmental System, Pusan National University) ;
  • Lee, Soon-Hwan (Department of Earth Science Education, Pusan National University) ;
  • Kim, Hyun-Goo (Korea Institute of Energy Research)
  • 유정우 (부산대학교 지구환경시스템학부) ;
  • 박순영 (부산대학교 환경연구원) ;
  • 전원배 (부산대학교 환경연구원) ;
  • 김동혁 (충남연구원) ;
  • 이화운 (부산대학교 지구환경시스템학부) ;
  • 이순환 (부산대학교 지구과학교육과) ;
  • 김현구 (한국에너지기술연구원 신재생에너지 지원센터)
  • Received : 2017.05.30
  • Accepted : 2017.07.27
  • Published : 2017.10.31

Abstract

In this study, we investigated the effect of aerosol feedback on $PM_{10}$ simulation using a two-way coupled air quality model (WRF-CMAQ). $PM_{10}$ concentration over Korea in January 2014 was simulated, and the aerosol feedback effect on the simulated solar radiation was intensively examined. Two $PM_{10}$ simulations were conducted using the WRF-CMAQ model with (FB) and without(NFB) the aerosol feedback option. We find that the simulated solar radiation in the west part of Korea decreased by up to $-80MJ/m^2$ due to the aerosol feedback effect. The feedback effect was significant in the west part of Korea, showing high $PM_{10}$ estimates due to dense emissions and its long-range transport from China. The aerosol feedback effect contributed to the decreased rRMSE(relative Root Mean Square Error) for solar radiation (47.58% to 30.75%). Aerosol feedback effect on the simulated solar radiation was mainly affected by concentration of $PM_{10}$. Moreover, FB better matched the observed solar radiation and $PM_{10}$ concentration than NFB, implying that taking into account the aerosol direct effects resulted in the improved modeling performance. These results indicate that aerosol feedback effects can play an important role in the simulation of solar radiation over Korean Peninsula.

Keywords

WRF-CMAQ two-way coupled model;aerosol feedback;solar radiation;rRMSE

Acknowledgement

Supported by : 한국에너지기술연구원

References

  1. Bowden, J.H., T.L. Otte, C.G. Nolte, and M.J Otte (2012) Examining interior grid nudging techniques using two-way nesting in the WRF model for regional climate modeling, Journal of Climate, 25, 2805-2823. https://doi.org/10.1175/JCLI-D-11-00167.1
  2. Forkel, R., J. Werhahn, A.B. Hansen, S. McKeen, S. Peckham, G. Grell, and P. Suppan (2012) Effect of aerosolradiation feedback on regional air quality - A case study with WRF/Chem, Atmospheric Environment, 53, 202-211. https://doi.org/10.1016/j.atmosenv.2011.10.009
  3. Hogrefe, C., G. Pouliot, D. Wong, A. Torian, S. Roselle, J. Pleim, and R. Mathur (2015) Annual application and evaluation of the online coupled WRF-CMAQ system over North America under AQMEII phase 2, Atmospheric Environment, 115, 683-694. https://doi.org/10.1016/j.atmosenv.2014.12.034
  4. Iacono, M.J., J.S. Delamere, E.J. Mlawer, M.W. Shephard, S.A. Clough, and W.D. Collins (2008) Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models, Journal of Geophysical Research, 113, D13103, doi:10.1029/2008JD009944. https://doi.org/10.1029/2008JD009944
  5. IPCC (2007) Climate change 2007: The physical science basis, Cambridge University Press, Cambridge and New York, 996pp.
  6. Jacob, D.J. and D.A. Winner (2009) Effect of climate change on air quality, Atmospheric Environment, 43, 51-63. https://doi.org/10.1016/j.atmosenv.2008.09.051
  7. Jacobson, M.Z., Y.J. Kaufmann, and Y. Rudich (2007) Examining feedbacks of aerosols to urban climate with a model that treats 3-D clouds with aerosol inclusions, Journal of Geophysical Research, 112(24), D24205, doi:10.1029/2007JD008922. https://doi.org/10.1029/2007JD008922
  8. Kong, X., R. Forkel, R.S. Sokhi, P. Suppan, A. Baklanov, M. Gauss, D. Brunner, R. Baro, A. Balzarini, C. Chemel, G. Curci, P. Jimenez-Guerrero, M. Hirtl, L. Honzak, U. Im, J.L. Perez, G. Pirovano, R. San Jose, K.H. Schlunzen, G. Tsegas, P. Tuccella, J. Werhahn, R. Zabkar, and S. Galmarini (2014) Analysis of meteorology-chemistry interactions during air pollution episodes using online coupled models within AQMEII phase-2, Atmospheric Environment, 115, 527-540.
  9. Koo, Y.S., S.T. Kim, H.Y. Yun, J.S. Han, J.Y. Lee, K.H. Kim, and E.C. Jeon (2008) The simulation of aerosol transport over East Asia region, Atmospheric Research, 90, 264-271. https://doi.org/10.1016/j.atmosres.2008.03.014
  10. Thiebaux, J., E. Rogers, W. Wang, and B. Katz (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
  11. Werner, M., M. Kryza, A.C. Skjoth, K. Walaszek, A.J. Dore, and H. Ojrzynska (2016) Aerosol-radiation feedback and $PM_{10}$ air concentrations over Poland, Pure and Applied Geophysics, 174(2), 551-568, doi:10.1007/s00024-016-1267-2. https://doi.org/10.1007/s00024-016-1267-2
  12. Wong, D.C., J. Pleim, R. Mathur, F. Binkowski, T. Otte, R. Gilliam, G. Pouliot, A. Xiu, J.O. Young, and D. Kang (2012) WRF-CMAQ two-way coupled system with aerosol feedback: software development and preliminary results, Geoscientific Model Development, 5, 299-312. https://doi.org/10.5194/gmd-5-299-2012
  13. Zhang, Y. (2008) Online coupled meteorology and chemistry models: history, current status, and outlook, Atmospheric Chemistry and Physics, 8, 2895-2932. https://doi.org/10.5194/acp-8-2895-2008