Atmosphere (대기)

Korean Meteorological Society (한국기상학회)
권호 표지
DOI QR코드

DOI QR Code

Construction and Case Analysis of Detailed Urban Characteristic Information on Seoul Metropolitan Area for High-Resolution Numerical Weather Prediction Model

고해상도 수치예보모델을 위한 수도권지역의 상세한 도시특성정보 구축 및 사례 분석

  • Lee, Hankyung (Air Quality Forecasting Center, Climate and Air Quality Research Department, National Institute of Environmental Research) ;
  • Jee, Joon-Bum (Research Center for Atmospheric Environment, Hankuk University of Foreign Studies) ;
  • Yi, Chaeyeon (Research Center for Atmospheric Environment, Hankuk University of Foreign Studies) ;
  • Min, Jae-Sik (Research Center for Atmospheric Environment, Hankuk University of Foreign Studies)
  • 이한경 (국립환경과학원 기후대기연구부 대기질통합예보센터) ;
  • 지준범 (한국외국어대학교 대기환경연구센터) ;
  • 이채연 (한국외국어대학교 대기환경연구센터) ;
  • 민재식 (한국외국어대학교 대기환경연구센터)
  • Received : 2019.08.08
  • Accepted : 2019.11.29
  • Published : 2019.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

In this study, the high-resolution numerical simulations considering detailed anthropogenic heat, albedo, emission and roughness length are analyzed by using single layer Urban Canopy Model (UCM) in Weather Research Forecast (WRF). For this, improved urban parameter data for Seoul Metropolitan Area (SMA) was collected from global data. And then the parameters were applied to WRF-UCM model after it was processed into 2-dimensional topographical data. The 6 experiments were simulated by using the model with each parameter and verified against observation from Automated Weather Station (AWS) and flux tower for the temperature and sensible heat flux. The data for sensible heat flux of flux towers on Jungnang and Bucheon, the temperature of AWS on Jungnang, Gangnam, Bucheon and Neonggok were used as verification data. In the case of summer, the improvement of simulation by using detailed anthropogenic heat was higher than the other experiments in sensible flux simulation. The results of winter case show improved in all simulations using each advanced parameters in temperature and sensible heat flux simulation. Improvement of urban parameters in this study are possible to reflect the heat characteristics of urban area. Especially, detailed application of anthropogenic heat contributed to the enhancement of predicted value for sensible heat flux and temperature.

Keywords

References

  1. Adachi, S. A., F. Kimura, H. Kusaka, M. G. Duda, Y. Yamagata, H. Seya, K. Nakamichi, and T. Aoyagi, 2014: Moderation of summertime heat island phenomena via modification of the urban form in the Tokyo metropolitan area. J. Appl. Meteor. Climatol., 53, 1886-1900, doi:10.1175/JAMC-D-13-0194.1.
  2. Arya, S. P., 2001: Introduction to Micrometeorology 2nd Edition. Academic press, New York, USA, 420 pp.
  3. Bhati, S., and M. Mohan, 2016: WRF model evaluation for the urban heat island assessment under varying land use/land cover and reference site conditions. Theor. Appl. Climatol., 126, 385-400, doi:10.1007/s00704-015-1589-5.
  4. Byon, J. Y., Y. J. Choi, and B. G. Seo, 2010: Evaluation of urban weather forecast using WRF-UCM (Urban Canopy Model) over Seoul. Atmosphere, 20, 13-26 (in Korean with English abstract).
  5. Chen, F., X. Yang, and W. Zhu, 2014: WRF simulations of urban heat island under hot-weather synoptic conditions: The case study of Hangzhou city, China. Atmos. Res., 138, 364-377, doi:10.1016/j.atmosres.2013.12.005.
  6. Chen, G., L. Zhao, and A. Mochida, 2016: Urban heat island simulations in Guangzhou, China, using the coupled WRF/UCM model with a land use map extracted from remote sensing data. Sustainability, 8, 628, doi:10.3390/su8070628.
  7. Chu, X., L. Xue, B. Geerts, R. Rasmussen, and D. Breed, 2014: A case study of radar observations and WRF LES simulations of the impact of ground-based glaciogenic seeding on orographic clouds and precipitation. Part I: Observations and model validations. J. Appl. Meteor. Climatol., 53, 2264-2286, doi:10.1175/JAMC-D-14-0017.1.
  8. Dong, Y., A. C. G. Varquez, and M. Kanda, 2016: 1-km global anthropogenic heat flux database for urban climate studies. Extended Abstract, AGU Fall Meeting 2016, B33H-0715.
  9. Dong, Y., A. C. G. Varquez, and M. Kanda, 2017: Global anthropogenic heat flux database with high spatial resolution. Atmos. Environ., 150, 276-294, doi:10.1016/j.atmosenv.2016.11.040.
  10. Grossman-Clarke, S., J. A. Zehnder, T. Loridan, and C. S. B. Grimmond, 2010: Contribution of land use changes to near-surface air temperatures during recent summer extreme heat events in the Phoenix metropolitan area. J. Appl. Meteor. Climatol., 49, 1649-1664, doi: 10.1175/2010JAMC2362.1.
  11. Gross, G., 2014: On the parametrization of urban land use in mesoscale models. Bound.-Layer Meteor., 150, 319-326, doi:10.1007/s10546-013-9863-5.
  12. Hong, S.-O., J.-Y. Byon, H. Park, Y.-G. Lee, B.-J. Kim, and J.-C. Ha, 2018: Sensitivity analysis of near surface air temperature to land cover change and urban parameterization scheme using unified model. Atmosphere, 28, 427-441, doi:10.14191/Atmos.2018.28.4.427 (in Korean with English abstract).
  13. Jee, J.-B., M. Jang, C. Yi, I.-S. Zo, B.-Y. Kim, M.-S. Park, and Y.-J. Choi, 2016: Sensitivity analysis of the highresolution WISE-WRF model with the use of surface roughness length in Seoul metropolitan areas. Atmosphere, 26, 111-126, doi:10.14191/Atmos.2016.26.1.111 (in Korean with English abstract).
  14. Jeong, J. C., 2009: Comparison of land surface temperatures derived from surface emissivity with urban heat island effect. J. Environ. Impact Assess., 18, 219-227 (in Korean with English abstract).
  15. Kang, M. S., J. Kim, H. S. Kim, B. M. Thakuri, and J. H. Chun, 2014: On the nighttime correction of $CO_2$ flux measured by eddy covariance over temperate forests in complex terrain. Kor. J. Agric. Forest Meteor., 16, 233-245 (in Korean with English abstract). https://doi.org/10.5532/KJAFM.2014.16.3.233
  16. Koo, H.-J., and Y.-H., Ryu, 2012: Impacts of anthropogenic heating on urban boundary layer in the Gyeong-In region. J. Environ. Impact Assess., 21, 665-681 (in Korean with English abstract). https://doi.org/10.14249/EIA.2012.21.5.665
  17. Kusaka, H., 2009: About a regional atmospheric model, WRF. J. Japan Soc. Fluid Mech., 28, 3-12 (in Japanese).
  18. Kusaka, H., and F. Kimura, 2004: Coupling a single-layer urban canopy model with a simple atmospheric model: Impact on urban heat island simulation for an idealized case. J. Meteor. Soc. Japan, 82, 67-80. https://doi.org/10.2151/jmsj.82.67
  19. Kusaka, H., H. Kondo, Y. Kikegawa, and F. Kimura, 2001: A simple single-layer urban canopy model for atmospheric models: comparison with multi-layer and slab models. Bound.-Layer Meteor., 101, 329-358. https://doi.org/10.1023/A:1019207923078
  20. Kwon, T. H., M.-S. Park, C. Yi, and Y. J. Choi, 2014: Effects of different averaging operators on the urban turbulent fluxes. Atmosphere, 24, 197-206, doi:10.14191/Atmos.2014.24.2.197 (in Korean with English abstract).
  21. Lee, B.-R., D.-G. Lee, K.-Y. Nam, Y.-G. Lee, and B.-J. Kim, 2015: Study on heat environment changes in Seoul metropolitan area using WRF-UCM: A comparison between 2000 and 2009. Atmosphere, 25, 483-499, doi:10.14191/Atmos.2015.25.3.483 (in Korean with English abstract).
  22. Lee, H., J.-B. Jee, and J.-S. Min, 2017: A study on highresolution numerical simulation with detailed classification of landuse and anthropogenic heat in Seoul metropolitan area. Kor. J. Agric. Forest Meteor., 19, 323-336 (in Korean with English abstract).
  23. Lee, H., J.-B. Jee, and J.-S. Min, S. Kim, and J. H. Chae, 2018: Analysis of meteorological and radiation characteristics using WISE observation data. J. Kor. Earth Sci. Soc., 39, 89-102 (in Korean with English abstract). https://doi.org/10.5467/JKESS.2018.39.1.89
  24. Macdonald, R. W., R. F. Griffiths, and D. J. Hall, 1998: An improved method for the estimation of surface roughness of obstacle arrays. Atmos. Environ., 32, 1857-1864. https://doi.org/10.1016/S1352-2310(97)00403-2
  25. Park, M. S., 2018: Overview of meteorological surface variables and boundary-layer structures in the Seoul metropolitan area during the MAPS-Seoul campaign. Aerosol Air Qual. Res., 18, 2157-2172, doi:10.4209/aaqr.2017.10.0428.
  26. Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, M. G. Duda, X.-Y. Huang, W. Wang, and J. G. Powers, 2008: A description of the advanced research WRF version 3. NCAR Technical Note-475+STR, 113 pp.
  27. Tewari, M., F. Chen, and H. Kusaka, 2006: Implementation and evaluation of a single-layer urban canopy model in WRF/Noah. Preprints, WRF users workshop 2006 [Available online at http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.470.716&rep=rep1&type=pdf].
  28. Vahmani, P., and T. S. Hogue, 2015: Urban irrigation effects on WRF-UCM summertime forecast skill over the Los Angeles metropolitan area. J. Geophys. Res. Atmos., 120, 9869-9881, doi:10.1002/2015JD023239.
  29. Vahmani, P., and G. A. Ban Weiss, 2016: Impact of remotely sensed albedo and vegetation fraction on simulation of urban climate in WRF-urban canopy model: A case study of the urban heat island in Los Angeles. J. Geophys. Res. Atmos., 121, 1511-1531, doi:10.1002/2015JD023718.
  30. Yi, C., T.-H. Kwon, M.-S. Park, Y. J. Choi, and S. M. An, 2015: A study on the roughness length spatial distribution in relation to the Seoul building morphology. Atmosphere, 25, 339-351, doi:10.14191/Atmos.2015.25.2.339 (in Korean with English abstract).