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http://dx.doi.org/10.14191/Atmos.2015.25.2.309

Sensitivity Test of the Numerical Simulation with High Resolution Topography and Landuse over Seoul Metropolitan and Surrounding Areas  

Park, Sung-Hwa (Weather Information Service Engine, Hankuk University of Foreign Studies)
Jee, Joon-Bum (Weather Information Service Engine, Hankuk University of Foreign Studies)
Yi, Chaeyeon (Weather Information Service Engine, Hankuk University of Foreign Studies)
Publication Information
Atmosphere / v.25, no.2, 2015 , pp. 309-322 More about this Journal
Abstract
The objective of this study is to evaluate the impact of the high resolution topographies and landuses data on simulated meteorological variables (wind speed at 10 m, temperature at 2 m and relative humidity at 2 m) in WRF. We compare the results with WRF simulation using each resolution of the topographies and landuses, and with 37 AWS observation data on the Seoul metropolitan regions. According to results of using high-resolution topography, WRF model gives better topographical expression over domain. And we can separate more detail (Low intensity residential, high intensity residential, industrial or commercial) using high resolution landuses data. The result shows that simulated temperature and wind speed are generally higher than AWS observation data. However, simulation trend with temperature, wind speed, and relative humidity are similar to observation data. The reason for that is that the high precipitation event occurred in CASE 1 and 2. Temperature have correlation of 0.43~0.47 and standard deviation of $2.12{\sim}2.28^{\circ}C$ in CASE 1, while correlation of more than 0.8 and standard deviation of $3.05{\sim}3.18m\;s^{-1}$ in CASE 2. In case of wind speed, correlation have lower than 0.5 and Standard Deviation of $1.88{\sim}2.34m\;s^{-1}$ in CASE 1 and 2. In statistical analysis shows that using highest resolution (U01) results are more close to the AWS observation data. It can be concluded that the topographies and landuses are important factor that affect model simulation. However, the tendency to always use high resolution topographies and landuses data appears to be unjustified, and optimal solution depends on the combination of scale effect and mechanisms of dynamic models.
Keywords
High resolution topographies and landuses; WRF; Seoul metropolitan areas;
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1 Allwine, K. J., J. H. Shinn, G. E. Streit, K. L. Clawson, and M. Brown, 2002: Overview of URBAN 2000: A multiscale field study of dispersion through an urban environment. Bull. Amer. Meteor. Soc., 83, 521-536.   DOI
2 Baik, J.-J., Y.-H. Kim, and H.-Y. Chun, 2001: Dry and moist convection forced by an urban heat island. J. Appl. Meteorol., 40, 1462-1475.   DOI
3 CGIAR-CSI, 2012: SRTM 90m Digital Elevation Data. http://srtm.csi.cgiar.org/index.asp.
4 Choi, Y. J., S. L. Kang, J. K. Hong, S. Grimmond, and K. J. Davis, 2013: A next-generation Weather Information Service Engine (WISE) customized for urban and surrounding rural areas. Bull. Amer. Meteor. Soc., 94, ES114-ES117.
5 De Meij, A., and J. F. Vinuesa, 2014: Impact of SRTM and corine land cover data on meteorological parameters using WRF. Atmos. Res., 143, 351-370.   DOI
6 Dupont, E., L. Menut, B. Carissimo, J. Pelon, and P. Flamant, 1999: Comparison between atmospheric boundary layer in Paris and its rural suburbs during the ECLAP experiment. Atmos. Environ., 33, 979-994, 1999.   DOI
7 Draxler, R. R., 1986: Simulated and observed influence of the nocturnal urban heat island on the local wind field. J. Climate Appl. Meteor., 25, 1125-1133.   DOI
8 Garstang, M., P. D. Tyson, and G. D. Emmitt, 1975: The structure of heat islands. Rev. Geophys. Space Phys., 13, 139-165.   DOI
9 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 Ha, W. S., and J. G. Lee, 2011: WRF sensitivity experiments on the choice of land cover data an event of sea breeze over the Yeongdong region. Atmosphere, 214, 373-389 (in Korean with English abstract).
11 Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 2318-2341.   DOI
12 Jee, J.-B., and Y.-J., Choi, 2014: Conjugation of landsat data for analysis of the land surface properties in capital area. J. Korean Earth Sci. Soc., 35, 54-68.   DOI
13 Kabat, P., and Coauthors, 2002: Vegetation, water, humans and the climate change: A new perspective on an interactive system. Springer, Heidelberg, Germany, 566 pp.
14 Kang, J.-H., M.-S. Suh, and C.-H. Kwak, 2007: Comparison of the land cover data sets over Asian region: USGS, IGBP, and UMd. Atmosphere, 17, 159-169 (in Korean with English abstract).
15 Kim, Y.-H., and J.-J. Baik, 2005: Spatial and temporal structure of the urban heat island in Seoul. J. Appl. Meteorol., 44, 593-605.
16 Kim, Y.-H., S.-B. Ryoo, J.-J. Baik, I.-S. Park, H.-J. Koo, and J.-C. Nam, 2008: Does the restoration of an inner-city stream in Seoul affect local thermal environment?. Theor. Appl. Climatol., 92, 239-248.   DOI
17 Landsberg, H. E., 1970: Man-made climate changes. Science, 170, 1265-1274.   DOI   ScienceOn
18 Lin, Y.-L., and R. B. Smith, 1986: Transient dynamics of airflow near a local heat source. J. Atmos. Sci., 43, 40-49.   DOI
19 Lee, S. H., S. W. Kim, W. M. Angevine, L. Bianco, S. A. McKeen, C. J. Senff, M. Trainer, S. C. Tucker, and R. J. Zamora, 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.   DOI
20 Lin, C. Y., F. Chen, J. Huang, W. C. Chen, Y. A. Liou, W. N. Chen, and S. C. Liu, 2008: Urban heat island effect and its impact on boundary layer development and land-sea circulation over northern Taiwan. Atmos. Environ., 42, 5635-5649.   DOI
21 Loveland, T. R., B. C. Reed, J. F. Brown, D. O. Ohlen, Z. Zhu, L. Yang, and J. W. Merchant, 2000: Development of a global land cover charcteristics data base and IGBP GISCover from 1 km AVHRR data. Int. J. Remote Sens., 18, 1251-1277.
22 Mestayer, P. G., and Coauthors, 2005: The urban boundary layer field campaign in Marseille (UBL/CLUESCOMPTE): Set-up and first results. Bound.-Layer Meteor., 114, 315-365.   DOI
23 Oke, 1982: The energetic basis of the urban heat island. Quart. J. Roy. Meteor. Soc., 108, 1-24.
24 Oke, 1987: Boundary Layer Climates. 2nd ed. Routledge, 435 pp.
25 Olfe, D. B., and R. L. Lee, 1971: Linearized calculations of urban heat island convection effects. J. Atmos. Sci., 28, 1374-1388.   DOI
26 Pleim, J. E., and J. S. Chang, 1992: A non-local closure model for vertical mixing in the convective boundary layer. Atmos. Environ., 26, 965-981.   DOI
27 Rotach, M. W., and Coauthors, 2005: BUBBLE-an urban boundary layer meteorology project. Theor. Appl. Climatol., 81, 231-261.   DOI
28 Shepherd, J. M., H. Pierce, and A. J. Negri, 2002: Rainfall modification by major urban areas: observations from spaceborne rain radar on the TRMM satellite. J. Appl. Meteorol., 41, 689-701.   DOI
29 Seo, B.-K., J. Y., Byon, and Y. J. Choi, 2010: Sensitivity evaluation of wind fields in surface layer by WRFPBL and LSM parameterizations. Atmosphere, 20, 319-332 (in Korean with English abstract).
30 Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, M. G. Duda, X. Huang, W. Wang, and J. G. Powers, 2008: A description of the advanced research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, National Center for Atmospheric Research, Boulder, CO, 125 pp.
31 Taylor, C. M., E. F. Lambin, N. Stephenne, R. J. Harding, and R. L. H. Essery, 2002: The influence of land use change on climate in the Sahel. J. Climate, 15, 3615-3629.   DOI
32 Xiu, A., and J. E. Pleim, 2001: Development of a land surface model. Part I: Application in a mesoscale meteorological model. J. Appl. Meteorol., 40, 192-209.   DOI
33 Zhang, C., H. Lin, M. Chen, and L. Yang, 2014: Scale matching of multiscale Digital Elevation Model (DEM) data the Weather Research and Forecasting (WRF) model: a case study of meteorological simulation in Hong Kong. Arab. J. Geosci., 7, 2215-2223.   DOI