DOI QR코드

DOI QR Code

High-resolution Meteorological Simulation Using WRF-UCM over a Coastal Industrial Urban Area

WRF-UCM을 이용한 연안산업도시지역 고해상도 기상 모델링

  • Bang, Jin-Hee (Environmental Health Center, University of Ulsan College of Medicine) ;
  • Hwang, Mi-Kyoung (Environmental Health Center, University of Ulsan College of Medicine) ;
  • Kim, Yangho (Environmental Health Center, University of Ulsan College of Medicine) ;
  • Lee, Jiho (Environmental Health Center, University of Ulsan College of Medicine) ;
  • Oh, Inbo (Environmental Health Center, University of Ulsan College of Medicine)
  • 방진희 (울산대학교 의과대학 환경보건센터) ;
  • 황미경 (울산대학교 의과대학 환경보건센터) ;
  • 김양호 (울산대학교 의과대학 환경보건센터) ;
  • 이지호 (울산대학교 의과대학 환경보건센터) ;
  • 오인보 (울산대학교 의과대학 환경보건센터)
  • Received : 2019.10.21
  • Accepted : 2020.01.09
  • Published : 2020.01.31

Abstract

High-resolution meteorological simulations were conducted using a Weather Research and Forecasting (WRF) model with an Urban Canopy Model (UCM) in the Ulsan Metropolitan Region (UMR) where large-scale industrial facilities are located on the coast. We improved the land cover input data for the WRF-UCM by reclassifying the default urban category into four detailed areas (low and high-density residential areas, commercial areas, and industrial areas) using subdivided data (class 3) of the Environmental and Geographical Information System (EGIS). The urban area accounted for about 12% of the total UMR and the largest proportion (47.4%) was in the industrial area. Results from the WRF-UCM simulation in a summer episode with high temperatures showed that the modeled temperatures agreed greatly with the observations. Comparison with a standard WRF simulation (WRF-BASE) indicated that the temporal and spatial variations in surface air temperature in the UMR were properly captured. Specifically, the WRF-UCM reproduced daily maximum and nighttime variations in air temperature very well, indicating that our model can improve the accuracy of temperature simulation for a summer heatwave. However, the WRF-UCM somewhat overestimated wind speed in the UMR largely due to an increased air temperature gradient between land and sea.

Keywords

References

  1. Borge, R., Alexandrov, V., Del Vas, J. J., Lumbreras, J., Rodriguez, E., 2008, A Comprehensive sensitivity analysis of the WRF model for air quality applications over the Iberian Peninsula, Atmos. Environ., 42, 8560-8574. https://doi.org/10.1016/j.atmosenv.2008.08.032
  2. Byon, J. Y., Choi, Y. J., Seo, B. G., 2010, Evaluation of urban weather forecast using WRF-UCM (Urban Canopy Model) over Seoul. Atmos., 20, 13-26.
  3. Chen, F., Dudhia, J., 2001, Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity, Mon. Weather Rev., 129, 569-585. https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2
  4. Chen, F., Kusaka, H., Bornstein, R., Ching, J., Grimmond, C. S. B., Grossman‐Clarke, S., Oridan, T., Manning, K. W., Martilli, A., Miao, S., Sailor, D., Salamanca, F. P., Taha, H., Tewari, M., Wang, X., Wyszogrodzki, A. A., Zhang, C., 2011, The integrated WRF/urban modelling system: development, evaluation, and applications to urban environmental problems, Int. J. Climat., 31, 273-288. https://doi.org/10.1002/joc.2158
  5. Chen, F., Xuchao Y., Weiping, Z., 2014, WRF simulations of urban heat island under hot-weather synoptic conditions: The case study of Hangzhou City, China., Atmos. res., 138, 364-377. https://doi.org/10.1016/j.atmosres.2013.12.005
  6. Clarke, R. H., Hess, G. D., 1975, On the relation between surface wind and pressure gradient, especially in lower latitudes, Bound-Lay. Meteorol., 9, 325-339. https://doi.org/10.1007/BF00230774
  7. Coutts, A. M., Beringer, J., Tapper, N. J., 2007, Impact of increasing urban density on local climate: Spatial and temporal variations in the surface energy balance in Melbourne, Australia, J. App. Meteorol. Clim., 46, 477-493. https://doi.org/10.1175/JAM2462.1
  8. Environmental Geographic Information Services (EGIS), 2019, http://egis.me.go.kr/map/map.do?type=land
  9. Farr, T. G., Kobrick, M., 2007, The shuttle radar topography mission, Rev. Geophys., 45, 1-33.
  10. Freitas, E. D., Rozoff, C. M., Cotton, W. R., Dias, P. L. S., 2007, Interactions of an urban heat island and sea-breeze circulations during winter over the metropolitan area of Sao Paulo, Brazil, Bound-Lay. Meteorol., 122, 43-65. https://doi.org/10.1007/s10546-006-9091-3
  11. Grimmond, C. S. B., Oke, T. R., 1999, Heat storage in urban areas: Local-scale observations and evaluation of a simple model, J. App. Meteorol., 38, 922-940. https://doi.org/10.1175/1520-0450(1999)038<0922:HSIUAL>2.0.CO;2
  12. Grimmond, S., 2007, Urbanization and global environmental change: local effects of urban warming, Geog. J., 173, 83-88. https://doi.org/10.1111/j.1475-4959.2007.232_3.x
  13. Grossman-Clarke, S., Zehnder, J. A., Loridan, T., Grimmond, C. S. B., 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. Climat., 49, 1649-1664. https://doi.org/10.1175/2010JAMC2362.1
  14. Hogrefe, C., Rao, S. T., Kasibhatla, P., Kallos, G., Tremback, C. J., Hao, W., Alapaty, K., 2001, Evaluating the performance of regional-scale photo -chemical modeling systems: Part I-Meteorological predictions. Atmos. Environ., 35, 4159-4174. https://doi.org/10.1016/S1352-2310(01)00182-0
  15. Holt, T., Pullen, J., 2007, Urban canopy modeling of the New York city metropolitan area: A comparison and validation of single-and multilayer parameterizations. Mon. Weather Rev., 135, 1906-1930. https://doi.org/10.1175/MWR3372.1
  16. Hwang, M. K., Kim, Y. K, Oh, I. B., Kang, Y. H., 2010, High-resolution simulation of meteorological fields over the coastal area with urban buildings, J. Korean Soc. Atmos. Environ., 26, 137-150. https://doi.org/10.5572/KOSAE.2010.26.2.137
  17. Industrial Land Information System (ILIS), 2019, https://www.industryland.or.kr/
  18. Jeong, J. H., Kim, Y. K., 2009, The application of high -resolution land cover and its effects on near-surface meteorological fields in tow different coastal areas, J. Korean Soc. Atmos. Environ., 25, 432-449. https://doi.org/10.5572/KOSAE.2009.25.5.432
  19. Jeong, J. H., Oh, I. B., Ko, D. K., Kim, Y. K., 2011, The characteristics of seasonal wind fields around the Pohang using cluster analysis and detailed meteorological model, J. Environ. Sci. Int., 20, 737-753. https://doi.org/10.5322/JES.2011.20.6.737
  20. Kim, H. O., Yeom, J. M., 2012, Effect of the urban land cover types on the surface temperature case study of Ilsan new city, Kor. J. Rem. Sens., 28, 203-214. https://doi.org/10.7780/kjrs.2012.28.2.203
  21. Kimura, F., Takahashi, S., 1991, The effects of land-use and anthropogenic heating on the surface temperature in the Tokyo metropolitan area: A numerical experiment, Atmos. Environ., 25, 155-164. https://doi.org/10.1016/0957-1272(91)90050-O
  22. Kinouchi, T., Yoshitani, J., 2001, Simulation of the urban heat island in Tokyo with future possible increases of anthropogenic heat, vegetation cover and water surface. Proceedings of 2001 International Symposium on Environmental Hydraulics, Arizona, USA.
  23. Kusaka, H., Chen, F., Tewari, M., Dudhia, J., Gill, D. O., Duda, M. G., Wang, W., Miya, Y., 2012, Numerical simulation of urban heat island effect by the WRF model with 4-km grid increment: An inter-comparison study between the urban canopy model and slab model, J. Meteor. Soc. Japan. Ser. II, 90, 33-45.
  24. Lee, B. R., Lee, D. G., Nam, K. Y., Lee, Y. G., Kim, B. J., 2015, Study on heat environment changes in Seoul metropolitan area using WRF-UCM: A comparison between 2000 and 2009, Atmos., 25, 483-499. https://doi.org/10.14191/Atmos.2015.25.3.483
  25. Lee, S. H., Kim, S. W., Angevine, W. M., Bianco, L., McKeen, S. A., Senff, C. J., Trainer, M., Tucker, S. C., Zamora, R. J., 2011, Evaluation of urban surface parameterizations in the WRF model using measurements during the Texas Air Quality Study 2006 field campaign, Atmos. Chem. Phys., 11, 2127-2143. https://doi.org/10.5194/acp-11-2127-2011
  26. Lee, S. H., Song, C. K., Baik, J. J., Park, S. U., 2009, Estimation of anthropogenic heat emission in the Gyeong-In region of Korea, Theor. Appl. Climat., 96, 291-303. https://doi.org/10.1007/s00704-008-0040-6
  27. Li, D., Bou-Zeid, E., Baeck, M. L., Jessup, S., Smith, J. A., 2013, Modeling land surface processes and heavy rainfall in urban environments: Sensitivity to urban surface representations, J. Hydrometeorol., 14, 1098-1118. https://doi.org/10.1175/JHM-D-12-0154.1
  28. Ma, S., Pitman, A., Hart, M., Evans, J. P., Haghdadi, N., MacGill, I., 2017, The impact of an urban canopy and anthropogenic heat fluxes on Sydney's climate, Int. J. Climatol., 37, 255-270. https://doi.org/10.1002/joc.5001
  29. Mahfouf, J. F., Richard, E., Mascart, P., 1987, The influence of soil and vegetation on the development of mesoscale circulations, J. Clim. Appl. Meteorol., 26, 1483-1495. https://doi.org/10.1175/1520-0450(1987)026<1483:TIOSAV>2.0.CO;2
  30. Miao, S., Li, P., Wang, X., 2009, Building morphological characteristics and their effect on the wind in Beijing. Advances in Atmos. Sci., 26, 1115. https://doi.org/10.1007/s00376-009-7223-7
  31. National Centers for Environmental Information (NOAA), 2019, https://www.ncdc.noaa.gov/data-access/model-data/model-datasets/global-forcast-system-gfs
  32. Oh, I. B., Bang, J. H., Kim, Y. H., 2015, Meteorological characteristics in the Ulsan metropolitan region: Focus on air temperature and winds, J. Korean Soc. Atmos. Environ., 31, 181-194. https://doi.org/10.5572/KOSAE.2015.31.2.181
  33. Oke, T. R., 1995, The heat island of the urban boundary layer: characteristics, causes and effects. In wind climate in cities, Springer Netherlands. 81-107.
  34. Palau, J. L., Perez-Landa, G., Dieguez, J. J., Monter, C., Millan, M. M., 2005, The importance of meteoro -logical scales to forecast air pollution scenarios on coastal complex terrain. Atmos. Chem. Phys., 5, 2771-2785. https://doi.org/10.5194/acp-5-2771-2005
  35. Park, S. Y., Lee, H. W., Kim, D. H., Lee, S. H., 2010, Numerical study on wind resources and forecast around coastal area applying inhomogeneous data to variational data assimilation, J. Environ. Sci. Int., 19, 983-999. https://doi.org/10.5322/JES.2010.19.8.983
  36. Rizwan, A. M., Dennis, L. Y., Chunho, L. I. U., 2008, A Review on the generation, determination and mitigation of Urban Heat Island, J. Environ. Sci., 20, 120-128. https://doi.org/10.1016/S1001-0742(08)60019-4
  37. Sharma, A., Fernando, H. J., Hellmann, J., Chen, F., 2014, Sensitivity of WRF model to urban parameterizations, with applications to Chicago metropolitan urban heat island, ASME 2014 4th Joint US-European Fluids Engineering Division Summer Meeting collocated with the ASME 2014 12th International Conference on Nanochannels, Microchannels, and Minichannels, Chicago, Illinois, USA.
  38. Song, B. G., Park, K. H., 2013, Air ventilation evaluation at nighttime for the construction of wind corridor in urban area, J. Korean Assoc. Geogr. Inf. Stud., 16, 16-29. https://doi.org/10.11108/kagis.2013.16.2.016
  39. Suzuki, R., 1991, The response of the surface wind speed to the synoptic pressure gradient in central Japan, J. Meteor. Soc. Japan. Ser. II, 69, 389-399. https://doi.org/10.2151/jmsj1965.69.3_389
  40. Yi, C., An, S. M., Kim, K., Kwon, H. G., Min, J. S., 2016, Surface micro-climate analysis based on urban morphological characteristics: Temperature deviation estimation and evaluation, Atmos., 26, 445-459. https://doi.org/10.14191/Atmos.2016.26.3.445
  41. Yoshikado, H., 1994, Interaction of the sea breeze with urban heat islands of different sizes and locations, J. Meteor. Soc. Japan, 72, 139-143. https://doi.org/10.2151/jmsj1965.72.1_139
  42. Zhang, H., Pu, Z., Zhang, X., 2013, Examination of errors in near-surface temperature and wind from WRF numerical simulations in regions of complex terrain, Weather and Forecasting, 28, 893-914. https://doi.org/10.1175/WAF-D-12-00109.1
  43. Zhou, X., Chen, H., 2018, Impact of urbanization-related land use land cover changes and urban morphology changes on the urban heat island phenomenon, Sci. Total Environ., 635, 1467-1476. https://doi.org/10.1016/j.scitotenv.2018.04.091