Journal of Environmental Science International (한국환경과학회지)

The Korean Environmental Sciences Society (한국환경과학회)
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Sensitivity Analysis of the WRF Model according to the Impact of Nudging for Improvement of Ozone Prediction

오존농도 예측 정확도 향상을 위한 자료동화기법에 따른 WRF모델의 기상민감도 연구

  • Kim, Taehee (Division of Earth Environmental System, Pusan National University) ;
  • Jeong, Ju-Hee (Department of Atmospheric Sciences, Pusan National University) ;
  • Kim, Yoo-Keun (Department of Atmospheric Sciences, Pusan National University)
  • 김태희 (부산대학교 지구환경시스템학부) ;
  • 정주희 (부산대학교 대기환경과학과) ;
  • 김유근 (부산대학교 대기환경과학과)
  • Received : 2016.02.29
  • Accepted : 2016.04.07
  • Published : 2016.05.31
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Abstract

Sensitivity analysis of the WRF model according to the impact of nudging (e.g., nudging techniques and application domains) was conducted during high nocturnal ozone episode to improve the prediction of the regional ozone concentration in the southeastern coastal area of the Korean peninsula. The analysis was performed by six simulation experiments: (1) without nudging (e.g., CNTL case), (2) with observation nudging (ONE case) to all domains (domain 1~4), (3) with grid nudging (GNE case) to all domains, (4)~(6) with grid nudging to domain 1, domain 1~2 and domain 1~3, respectively (GNE-1, GNE-2, GNE-3 case). The results for nudging techniques showed that the GNE case was in very good agreement with those observed during all analysis periods (e.g., daytime, nighttime, and total), as compared to the ONE case. In particular, the large effect of grid nudging on the near-surface meteorological factors (temperature, relative humidity, and wind fields) was predicted at the coastline and nearby sea during daytime. The results for application domains showed that the effects of nudging were distinguished between the meteorological factors and between the time periods. When applied grid nudging until subdomain, the improvement effects of temperature and relative humidity had differential tendencies. Temperature was increased for all time, but relative humidity was increased in daytime and was decreased in nighttime. Thus, GNE case showed better result than other cases.

Keywords

References

  1. Barna, M., Lamb, B., 2000, Improving ozone modeling in regions of complex terrain using observational nudging in a prognostic meteorological model, Atmos. Environ., 34, 4889-4906. https://doi.org/10.1016/S1352-2310(00)00231-4
  2. Choi, H. J., Lee, H. W., Sung, K., Kim, M. J., 2009, The Effect of atmospheric flow field according to the radius influence and nudging coefficient of the objective analysis on complex area, Journal of the Environmental Sciences, 18(3), 271-281. https://doi.org/10.5322/JES.2009.18.3.271
  3. Choi, J. W., Lee, J. G., 2015, A Sensitivity study of WRF model simulations to nudging methods for a Yeongdong heavy snowfall event, Atmosphere, Korean Meteorological Society, 25(1), 99-115. https://doi.org/10.14191/Atmos.2015.25.1.099
  4. Dawson, J. P., Adams, P. J., Pandis, S. N., 2007, Sensitivity of ozone to summertime climate in the eastern USA: A Modeling case study, Atmospheric environment, 41(7), 1494-1511. https://doi.org/10.1016/j.atmosenv.2006.10.033
  5. Eliasson, I., Thorsson, S., Andersson-Skold, Y., 2003, Summer nocturnal ozone maxima in Goteborg, Sweden, Atmos. Environ., 37, 2615-2627. https://doi.org/10.1016/S1352-2310(03)00205-X
  6. Hanna, S. R., 1994, Mesoscale meteorological model evaluation techniques with emphasis on needs of air quality models, Meteorological Monographs: Mesoscale Modelling of the Atmosphere, 25.
  7. Jeon, B. I., 1999, Characteristics of nocturnal maximum ozone and meteorological relevance in Pusan coastal area, Journal of the Korean Environmental Sciences Society, 8(3), 287-292.
  8. Jeong, J. H., Lo, S., Song, S. K., Kim, Y. K., 2010, The Application of wind profiler data and its effects on wind distributions in two different coastal areas, Journal of the Environmental Sciences, 19(6), 689-701. https://doi.org/10.5322/JES.2010.19.6.689
  9. Jeong, Y. M., Lee, H. W., Lee, S. H., Choi, H. J., Jeon, W. B., 2011, Numerical study on the impact of regional warming on the meterological field and ozone concentration over the South-Eastern part of the Korean peninsula, Journal of the Environmental Sciences, 19(12), 1431-1445.
  10. Lee, S. H., Kim, H. S., Lee, H. W., 2004, Numerical study on surface data assimilation for estimation of air quality in complex terrain, J. Korean Soc. Atmos. Environ., 20(4), 523-537.
  11. Liu, P., Tsimpidi, A. P., Hu, Y., Stone, B., Russell, A. G., Nenes, A., 2012, Differences between downscaling with spectral and grid nudging using WRF, Atmos. Chem. Phys., 12, 3601-3610. https://doi.org/10.5194/acp-12-3601-2012
  12. Mao, Q., Gautney, L. L., Cook, T. M., Jacobs, M. E., Smith, S. M., Kelsoe, J. J., 2006, Numerical experiments on MM5-CMAQ sensitivity to various PBL schemes, Atmospheric Environment, 40(17), 3092-3110. https://doi.org/10.1016/j.atmosenv.2005.12.055
  13. Otte, T. L., 2008, The Impact of nudging in the meteorological model for retrospective air quality simulations, Part I : Evaluation against national observation networks, Journal of Applied Meteorology and Climatology, 47, 1853-1867. https://doi.org/10.1175/2007JAMC1790.1
  14. Park, J. H., 2006, Concentration characteristics and meteorological formation mechanism of nocturnal surface ozone in Busan coastal area, Pukyong National University, Master's degree.
  15. Pirovano, G., Coll, I., Bedogni, M., Alessandrini, S., Costa, M. P., Gabusi, V., Lasry, F., Menut, L., Vautard, R., 2007, On the influence of meteorological input on photochemical modeling of a severe episode over a coastal area, Atmos. Environ., 41, 6445-6464. https://doi.org/10.1016/j.atmosenv.2007.04.011
  16. Seaman, N. L., 2000, Meteorological modeling for air-quality assessments, Atmospheric Environment, 34(12-14), 2231-2259. https://doi.org/10.1016/S1352-2310(99)00466-5
  17. Stauffer, D. R., Seaman, N. L., Hunter, G. K., Leidner, S. M., Lario-Gibbs, A., 2000, A Field-coherence technique for meteorological field-program design for air quality studied, Part I : Description and interpretation, J. Appl. Meteor., 39, 297-316. https://doi.org/10.1175/1520-0450(2000)039<0297:AFCTFM>2.0.CO;2
  18. Taylor, K. E., 2001, Summarizing multiple aspects of model performance in a single diagram, J. Geophys. Res., 106 (D7), 7183-7192. https://doi.org/10.1029/2000JD900719
  19. U. S. EPA, 2007, Guidance on the use of models and other analyses for demonstrating attainment of air quality goals for ozone, PM2.5, and regional haze, Tech Rep., EPA-454/B-07-002, Research Triangle Park, NC.
  20. Yoon, M. J., 2009, The Sensitivity analysis of WRF model with various nudging methods and physics scheme, Master Dissertation, Anyang University, Korea.

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  1. Sensitivity Analysis of Ozone Simulation according to the Impact of Meteorological Nudging vol.32, pp.4, 2016, https://doi.org/10.5572/KOSAE.2016.32.4.372