Urban Surface Energy Balance Models: Model Characteristics and Methodology for a Comparison Study

  • C.S.B. GrimmondEmail author
  • Martin Best
  • Janet Barlow
  • A. J. Arnfield
  • J.-J. Baik
  • A. Baklanov
  • S. Belcher
  • M. Bruse
  • I. Calmet
  • F. Chen
  • P. Clark
  • A. Dandou
  • E. Erell
  • K. Fortuniak
  • R. Hamdi
  • M. Kanda
  • T. Kawai
  • H. Kondo
  • S. Krayenhoff
  • S. H. Lee
  • S.-B. Limor
  • A. Martilli
  • V. Masson
  • S. Miao
  • G. Mills
  • R. Moriwaki
  • K. Oleson
  • A. Porson
  • U. Sievers
  • M. Tombrou
  • J. Voogt
  • T. Williamson


Many urban surface energy balance models now exist. These vary in complexity from simple schemes that represent the city as a concrete slab, to those which incorporate detailed representations of momentum and energy fluxes distributed within the atmospheric boundary layer. While many of these schemes have been evaluated against observations, with some models even compared with the same data sets, such evaluations have not been undertaken in a controlled manner to enable direct comparison. For other types of climate model, for instance the Project for Intercomparison of Land-Surface Parameterization Schemes (PILPS) experiments (Henderson-Sellers et al., 1993), such controlled comparisons have been shown to provide important insights into both the mechanics of the models and the physics of the real world. This paper describes the progress that has been made to date on a systematic and controlled comparison of urban surface schemes. The models to be considered, and their key attributes, are described, along with the methodology to be used for the evaluation.


Heat Flux Latent Heat Flux Urban Heat Island Surface Energy Balance Urban Surface 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We wish to thank the UK Met Office, Vasilis Pappas (KCL), Rob Mullen (KCL), Robert Ewen (KCL), Professor Andy Pitman (Macquarie University) and Dr Catherine Souch (RGS-IBG) for their contributions to this project to date.


  1. Arnfield, A.J.: Estimation of diffuse irradiance on sloping, obstructed surfaces – an error analysis. Archives for Meteorology Geophysics and Bioclimatology Series B-Theoretical and Applied Climatology, 30, 303–320, 1982.CrossRefGoogle Scholar
  2. Arnfield, A.J.: A simple model of urban canyon energy budget and its validation, Phys. Geog., 21, 305–326, 2000.Google Scholar
  3. Baklanov, A., Mahura, A., Nielsen, N.W. and Petersen, C.: Approaches for urbanization of DMI-HIRLAM NWP model. HIRLAM Newsletter 49, pp. 61–75, 2006.Google Scholar
  4. Baklanov, A., Mestayer, P.G., Clappier, A., Zilitinkevich, S., Joffre, S., Mahura, A. and Nielsen, N.W.: Towards improving the simulation of meteorological fields in urban areas through updated/advanced surface fluxes description, Atmos. Chem. Phys., 8, 523–543, 2008.CrossRefGoogle Scholar
  5. Barlow, J.F. and Belcher, S.E.: A wind tunnel model for quantifying fluxes in the urban boundary layer, Bound.-Layer Meteorol., 104, 131–150, 2002.CrossRefGoogle Scholar
  6. Barlow, J.F., Harman, I.N. and Belcher, S.E.: Scalar fluxes from urban street canyons, Part I: Laboratory simulation, Bound.-Layer Meteorol., 113, 369–385, 2004.CrossRefGoogle Scholar
  7. Best, M.J., Grimmond, C.S.B. and Villani, M.G.: Evaluation of the urban tile in MOSES using surface energy balance observations, Bound.-Layer Meteorol., 118, 503–525, 2006.CrossRefGoogle Scholar
  8. Best, M.J.: Representing urban areas within operational numerical weather prediction models, Bound.-Layer Meteorol., 114, 91–109, 2005.CrossRefGoogle Scholar
  9. Best, M.J.: Progress towards better weather forecasts for city dwellers: from short range to climate change, Theo. Appl. Clim., 84, 47–55, 2006.CrossRefGoogle Scholar
  10. Bonacquisti, V., Casale, G.R., Palmieri, S. and Siani, A.M.: A canopy layer model and its application to Rome, Sci. Total Environ., 364, 1–13, 2006.CrossRefGoogle Scholar
  11. Bornstein, R. and Lin, Q.L.: Urban heat islands and summertime convective thunderstorms in Atlanta: three case studies, Atmos. Environ., 34, 507–516, 2000.CrossRefGoogle Scholar
  12. Bottema, M. Aerodynamic roughness parameters for homogeneous building groups. Part I: Theory, Document SUB-MESO # 18, Ecole Centrale de Nantes, 40 pp., 1995.Google Scholar
  13. Brown, M.J.: Urban parameterizations for mesoscale meteorological models. In Z. Boybeyi (ed.), Mesoscale Atmospheric Dispersion, Computational Mechanics, 2001.Google Scholar
  14. Bruse, M. and Fleer, H.: Simulating surface–plant–air interactions inside urban environments with a three dimensional numerical model, Environ. Modelling Software, 13, 373–384, 1998.CrossRefGoogle Scholar
  15. Clarke, J.A.: Energy Simulation in Building Design, Adam Hilger, Bristol, 362 pp., 1985.Google Scholar
  16. Dandou, A., Tombrou, M., Akylas, E., Soulakellis, N. and Bossioli, E.: Development and evaluation of an urban parameterization scheme in the Penn State/NCAR Mesoscale model (MM5), J. Geophys. Res., 110, D10102, 2005.Google Scholar
  17. de Bruin, H.A.R. and Holtslag, A.A.M.: A simple parameterization of surface fluxes of sensible and latent heat during daytime compared with the Penman–Monteith concept. J. Appl. Meteor., 21, 1610–1621, 1982.CrossRefGoogle Scholar
  18. Dudhia, J.: ‘A multi-layer soil temperature model for MM5’, Preprints, The Sixth PSU/NCAR Mesoscale Model Users’, Workshop, 22–24 July 1996, Boulder, Colorado, 49–50, 1996.Google Scholar
  19. Dupont, S. and Mestayer, P.G.: Parameterisation of the urban energy budget with the submesoscale soil model, J. Appl. Meteorol. Climatol., 45, 1744–1765, 2005.CrossRefGoogle Scholar
  20. Dupont, S., Mestayer, P.G., Guilloteau, E., Berthier, E. and Andrieu, H.: Parameterisation of the urban water budget with the submesoscale soil model, J. Appl. Meteorol. Climatol., 45, 624–648, 2006.CrossRefGoogle Scholar
  21. Erell, E. and Williamson, T.: Simulating air temperature in an urban street canyon in all weather conditions using measured data from a reference meteorological station, Int. J. Climatol. 26, 1671–1694, 2006.CrossRefGoogle Scholar
  22. Essery, R.L.H., Best, M.J., Betts, R.A., Cox, P.M. and Taylor, C.M.: Explicit representation of subgrid heterogeneity in a GCM land surface scheme, J. Hydrometeorol., 4, 530–543, 2003.CrossRefGoogle Scholar
  23. Fortuniak, K., Offerle, B. and Grimmond, C.S.B.: Slab surface energy balance scheme and its application to parameterisation of the energy fluxes on urban areas, NATO ASI, Kiev, Ukraine, 4-15.05 2004, 82–83, [] 2004.
  24. Fortuniak, K., Offerle, B. and Grimmond, C.S.B.: Application of a slab surface energy balance model to determine surface parameters for urban areas, Lund eRep. Phys. Geog., 5, 90–91, [] 2005.Google Scholar
  25. Garand, L.: Some improvements and complements to the infrared emissivity algorithm including a parameterization of the absorption in the continuum region, J. Atmos. Sci., 40, 230–244, 1983.CrossRefGoogle Scholar
  26. Grimmond, C.S.B.: The suburban energy balance: Methodological considerations and results for a mid-latitude west coast city under winter and spring conditions, Int. J Climatol., 12, 481–497, 1992.CrossRefGoogle Scholar
  27. Grimmond, C.S.B., Cleugh, H.A. and Oke, T.R.: An objective urban heat storage model and its comparison with other schemes. Atmos. Environ., 25B, 311–326, 1991.Google Scholar
  28. Grimmond, C.S.B. and Oke, T.R.: An evaporation-interception model for urban areas, Water Resour. Res., 27, 1739–1755, 1991.CrossRefGoogle Scholar
  29. Grimmond, C.S.B. and Oke, T.R.: Heat storage in urban areas: observations and evaluation of a simple model, J. Appl. Meteorol., 38, 922–940, 1999a.CrossRefGoogle Scholar
  30. Grimmond, C.S.B. and Oke, T.R.: Rates of evaporation in urban areas, International Association of Hydrological Sciences Publication, 259, 235–243, 1999b.Google Scholar
  31. Grimmond, C.S.B. and Oke, T.R.: Turbulent heat fluxes in urban areas: Observations and local-scale urban meteorological parameterization scheme (LUMPS), J. Appl. Meteorol., 41, 792–810, 2002.CrossRefGoogle Scholar
  32. Grimmond, C.S.B.: Urbanization and global environmental change: Local effects of urban warming, Geograph. J., 173, 83–88, 2007.CrossRefGoogle Scholar
  33. Guilloteau, E.: Optimized computation of transfer coefficients in surface layer with different momentum and heat roughness length, Bound. Layer Meteorol., 87, 147–160, 1998.CrossRefGoogle Scholar
  34. Hacker, J.N., Holmes, M.J., Belcher, S.E. and Davies, G.: Climate change and the internal environment of buildings: A designers guide, TM36, pp. 52. Chartered Inst. Building Services Eng. and Royal Inst. British Architects. ISBN: 190328750, 2004.Google Scholar
  35. Hagishima, A. and Tanimoto, J.: Field measurements for estimating the convective heat transfer coefficient at building surfaces, Build. Environ., 38, 873–881, 2003.CrossRefGoogle Scholar
  36. Hamdi, R.: Numerical study of the atmospheric boundary layer over urban areas: validations for the cities of Basel and Marseilles, PhD thesis, 34/2005 Catholic university of Louvain, Belgium, 2005.Google Scholar
  37. Hamdi, R. and Schayes, G.: Validation of the Martilli’s urban boundary layer scheme with measurements from two mid-lattitude European cities, Atmos. Chem. Phys., 7, 4513–4526, 2007.CrossRefGoogle Scholar
  38. Hamdi, R. and Masson, V.: Inclusion of a drag approach in the Town Energy Balance (TEB) scheme: offline 1-D evaluation in a street canyon, J. Appl. Meteor. Clim., 47, 2627–2644, 2008.Google Scholar
  39. Harman, I.N., Barlow, J.F. and Belcher, S.E.: Scalar fluxes from urban street canyons, Part II: Model, Bound.-Layer Meteorol., 113, 387–410, 2004b.CrossRefGoogle Scholar
  40. Harman, I.N., Best, M.J. and Belcher, S.E.: Radiative exchange in an urban street canyon, Bound.-Layer Meteorol., 110, 301–316, 2004a.CrossRefGoogle Scholar
  41. Harman, I.N., Belcher, S.E.: The surface energy balance and boundary layer over urban street canyons, Q. J. The Royal Meteorological Society, 132(621), 2749–2768, 2006.CrossRefGoogle Scholar
  42. Henderson-Sellers, A., Yang, Z.L. and Dickinson, R.E.: The project for intercomparison of land-surface parameterization schemes, Bull. AMS, 74, 1335–1349, 1993.Google Scholar
  43. Henderson-Sellers, A., Irannejad, P., McGuffie, K., and Pitman, A.: Predicting land-surface climates-better skill or moving targets? Geophys. Res. Lett., 30, 14, 1777, doi:10.1029/2003GL017387, 2003.CrossRefGoogle Scholar
  44. Ichinose, T., Shimodozono, K. and Hanaki, K.: Impact of anthropogenic heat on urban climate in Tokyo. Atmos. Environ., 33, 3897–3909, 1999.CrossRefGoogle Scholar
  45. IPCC: Third Assessment Report: Climate Change 2001, ed. Watson, R.T. and core writing team, IPCC, Geneva, Switzerland, pp. 184, 2001.Google Scholar
  46. Irranejad, P., Henderson-Sellers, A., Sharmeen, S.: Importance of land-surface parameterization for latent heat simulation in global atmospheric models, Geophys. Res. Lett., 30, 17, 1904, doi:10.1029/2003/GL018044, 2003.Google Scholar
  47. Johnson, G.T., Oke, T.R., Lyons, T.J., Steyn, D.G., Watson, I.D., Voogt, J.A.: Simulation of surface urban heat islands under ideal conditions at night. 1. Theory and tests against field data, Bound.-Layer Meteorol., 56(3), 275–294, 1991.CrossRefGoogle Scholar
  48. Kanda, M., Kawai, T., Kanega, M., Moriwaki, R., Narita, K. and Hagishima, A.: A simple energy balance model for regular building arrays, Bound.-Layer Meteorol., 116, 423–443, 2005a.CrossRefGoogle Scholar
  49. Kanda, M., Kawai, T., Nakagawa, K.: A simple theoretical radiation scheme for regular building arrays. Bound.-Layer Meteorol., 114, 71–90, 2005b.CrossRefGoogle Scholar
  50. Kondo, H. and Liu, F.H.: A study on the urban thermal environment obtained through a one-dimensional urban canopy model, J. Jpn. Soc. Atmos. Environ., 33, 179–192, 1998 (in Japanese).Google Scholar
  51. Kondo, H., Genchi, Y., Kikegawa, Y., Ohashi, Y., Yoshikado, H. and Komiyama, H.: Development of a multi-layer urban canopy model for the analysis of energy consumption in a big city: Structure of the urban canopy model and its basic performance. Bound.-Layer Meteorol., 116, 395–421, 2005.CrossRefGoogle Scholar
  52. Krayenhoff, E.S., Voogt, J.A.: A microscale three-dimensional urban energy balance model for studying surface temperatures, Bound.-Layer Meteorol., 123, 433–461, 2007.CrossRefGoogle Scholar
  53. Kusaka, H., Kondo, H., Kikegawa, Y. and Kimura, F.: A simple single-layer urban canopy model for atmospheric models: comparison with multi-layer and slab models, Bound.-Layer Meteorol., 101, 329–358, 2001.CrossRefGoogle Scholar
  54. Lee, S.-H. and Park, S.-U.: A vegetated urban canopy model for meteorological and environmental modelling, Bound.-Layer Meteorol., 126, 73–102, 2008.Google Scholar
  55. Lemonsu, A., Grimmond, C.S.B. and Masson, V.: Modelling the surface energy balance of an old Mediterranean city core, J. Appl. Meteorol., 43, 312–327, 2004.CrossRefGoogle Scholar
  56. Macdonald, R.W., Griffith, R.F., Hall, D.J.: An improved method for estimation of surface roughness of obstacle arrays, Atmos. Environ., 32, 1857–1864, 1998.CrossRefGoogle Scholar
  57. Mahura, A., Baklanov, A., Petersen, C., Sattler, K., Amstrup, B. and Nielsen, N.W.: ISBA scheme performance in high resolution modelling for low winds conditions. HIRLAM Newsletter, 49, 22–35, 2006.Google Scholar
  58. Martilli, A.: Current research and future challenges in urban mesoscale modelling, Int. J. Climatol., 27, 1909–1918, 2007.CrossRefGoogle Scholar
  59. Martilli, A., Clappier, A. and Rotach, M.W.: An urban surface exchange parameterisation for mesoscale models, Bound.-Layer Meteorol., 104, 261–304, 2002.CrossRefGoogle Scholar
  60. Masson, V.: A physically-based scheme for the urban energy budget in atmospheric models, Bound.-Layer Meteorol., 41, 1011–1026, 2000.Google Scholar
  61. Masson, V.: Urban surface modeling and the meso-scale impact of cities, Theor. Appl. Climatol., 84, 35–45, 2006.CrossRefGoogle Scholar
  62. Masson, V., Grimmond, C.S.B. and Oke, T.R.: Evaluation of the Town Energy Balance (TEB) scheme with direct measurements from dry districts in two cities, J. Appl. Meteorol., 41, 1011–1026, 2002.Google Scholar
  63. Mills, G.: An urban canopy-layer climate model, Theor. Appl. Climatol., 57, 229–244, 1997.CrossRefGoogle Scholar
  64. Montávez, J.P., Jiménez, J.I. and Sarsa, A.: A monte carlo model of the nocturnal surface temperatures in urban canyons, Bound.-Layer Meteorol., 96, 433–452, 2000.CrossRefGoogle Scholar
  65. Monteith, J.L.: Evaporation and surface temperature, Q. J. Roy. Meteor. Soc. 107, 1–27, 1981.CrossRefGoogle Scholar
  66. Noilhan, J. and Planton, S.: A simple parameterization of land-surface processes for numerical meteorological models, Mon. Wea. Rev., 117, 536–549, 1989.CrossRefGoogle Scholar
  67. Offerle, B., Grimmond, C.S.B. and Oke, T.R.: Parameterization of net all-wave radiation for urban areas, J. Appl. Meteorol., 42, 1157–1173, 2003.CrossRefGoogle Scholar
  68. Offerle, B., Grimmond, C.S.B. and Fortuniak, K.: Heat storage and anthropogenic heat flux in relation to the energy balance of a central European city centre, Int. J. Climatol., 25, 1405–1419, 2006.CrossRefGoogle Scholar
  69. Oke, T.R.: City size and urban heat island, Atmos. Environ., 7, 769–779, 1973.CrossRefGoogle Scholar
  70. Oleson, K.W., Bonan, G.B., Feddema, J. and Vertenstein, M.: An urban parameterization for a global climate model: 2. Sensitivity to input parameters and the simulated heat island in offline simulations, J. Appl. Meteorol. Climatol., 47, 1061–1076, 2008a.Google Scholar
  71. Oleson. K.W., Bonan, G.B., Feddema, J., Vertenstein, M. and Grimmond, C.S.B.: An urban parameterization for a global climate model: 1. Formulation & evaluation, J. Appl. Meteorol. Climatol., 47, 1038–1060, 2008b.Google Scholar
  72. Qu, W.,. Henderson-Sellers, A., Pitman, A., Chen, T.H., Abramopoulos, F., Boone, A., Chang, S., Chen, F., Dai, Y., Dickinson, R.E., Dumenil, L., Ek, M., Gedney, N., Gusev, Y.M., Kim, J., Koster, R., Kowalczyk, E.A., Lean, J., Lettenmaier, D., Liang, X., Mahfouf, J.-F., Mengelkamp, H.-T., Mitchell, K., Nasonova, O.N., Noilhan, J., Robock, A., Rosenzweig, C., Schaake, J., Schlosser, C.A., Schulz, J.-P., Shmakin, A.B., Verseghy, D.L., Wetzel, P., Wood, E.F., Yang, Z.-L., Zeng, Q.: Sensitivity of latent heat flux from PILPS land-surface schemes to perturbations of surface air temperature, J. Atmos. Sci., 55, 1909–1926, 1998.CrossRefGoogle Scholar
  73. Raupach, M.R.: Simplified expressions for vegetation roughness length and zero-plane displacement, Bound. Layer Meteorol., 71, 211–216, 1994.CrossRefGoogle Scholar
  74. Raupach, M.R.: Corrigenda, Bound. Layer Meteorol., 76, 303–304, 1995.CrossRefGoogle Scholar
  75. Roth, M.: Review of atmospheric turbulence over cities, Q. J. Roy. Meteorol. Soc., 126, 941–990, 2000.CrossRefGoogle Scholar
  76. Rowley, F.B., Algren, A.B. and Blackshaw, J.L.: Surface conductances as affected by air velocity, temperature and character of surface. ASHRAE Trans., 36, 429–446, 1930.Google Scholar
  77. Savijärvi, H.: Fast radiation parameterization schemes for mesoscale and short-range forecast models, J. Appl. Meteorol., 29, 437–447, 1990.CrossRefGoogle Scholar
  78. Sailor, D.J. and Lu, L.A.: top-down methodology for developing diurnal and seasonal anthropogenic heating profiles for urban areas. Atmos. Environ., 38, 2737–2748, 2004.CrossRefGoogle Scholar
  79. Saitoh, T.S., Shimada, T. and Hoshi, H.: Modeling and simulation of the Tokyo urban heat island, Atmos. Environ., 30, 3431–3442, 1996.CrossRefGoogle Scholar
  80. Sakakibara, Y.: A numerical study of the effect of urban geometry upon the surface energy budget, Atmos. Environ., 30, 487–496, 1996.CrossRefGoogle Scholar
  81. Schlosser, C.A., Slater, A.G., Robock, A., Pitman, A., Vinnikov, K.Y., Henderson-Sellers, A., Speranskaya, N.A. and Mitchell, K.: PILPS 2(D) Contributers: Simulations of a Boreal Grassland Hydrology at Valdai, Russia: PILPS Phase 2(d), Mon. Wea. Rev., 128, 301–321, 2000.CrossRefGoogle Scholar
  82. Shao, Y. and Henderson-Sellers, A.: Modeling soil moisture : a project for intercomparison of land surface parameterization schemes Phase 2(b), JGR, 101, 7227–7250, 1996.CrossRefGoogle Scholar
  83. Shashua-Bar, L. and Hoffman, M.E.: The Green CTTC model for predicting the air temperature in small urban wooded sites, Build. Environ., 37, 1279–1288, 2002.CrossRefGoogle Scholar
  84. Shashua-Bar, L. and Hoffman, M.E.: Quantitative evaluation of passive cooling of the UCL microclimate in hot regions in summer, Build. Environ., 39, 1087–1099, 2004.CrossRefGoogle Scholar
  85. Sievers, U.: Verallgemeinerung der Stromfunktionsmethode auf drei Dimensionen, Meteorol. Zeitschrift, N.F. 4, 3–15, 1995.Google Scholar
  86. Stephens, G.L.: Radiation profiles in extended water clouds. II: Parameterization schemes, J. Atmos. Sci., 35, 2123–2132, 1978.CrossRefGoogle Scholar
  87. Taha, H.: Modifying a mesoscale meteorological model to better incorporate urban heat storage: A bulk parameterization approach, J. Appl. Meteorol., 38, 466–473, 1999.CrossRefGoogle Scholar
  88. Tanimoto, J., Hagishima, A. and Chimklai, P.: An approach for coupled simulation of building thermal effects and urban climatology, Energy Build., 36, 781–793, 2004.CrossRefGoogle Scholar
  89. Tian, W., Wang, Y., Xie, Y., Wu, D., Zhu, L. and Ren, J.: Effect of building integrated photovoltaics on microclimate of urban canopy layer, Build. Environ., 42, 1891–1901, 2007.CrossRefGoogle Scholar
  90. Tso, C.P., Chan, B.K. and Hashim, M.A.: Analytical solutions to the near-neutral atmospheric surface energy balance with and without heat storage for urban climatological studies, J. Appl. Meteorol., 30, 413–424, 1991.CrossRefGoogle Scholar
  91. Watson, R.T., Zinyowera, M.C. and Moss, R.H.: The Regional Impacts of Climate Change An Assessment of Vulnerability, [last accessed 8 Aug 2007] 1997.
  92. Yang, Z.-L. and Dickinson, R.E.: Preliminary study of spin-up processes in land surface models with the first stage data of Project for Intercomparison of Land Surface Parameterization Schemes Phase 1(a), JGR, 100, 16553–16578, 1995.CrossRefGoogle Scholar
  93. Zilitinkevich, S.S.: Non-local turbulent transport: pollution dispersion aspects of coherent structure of convective flows. In: H. Power, N. Moussiopoulos, and C.A. Brebbia (eds.), Air pollution III – Volume I. Air pollution theory and simulation, Computational Mechanics Publications, Southampton, Boston, 53–60, 1995.Google Scholar
  94. Zilitinkevich, S.S., Baklanov, A.A., Mammarella, I. and Joffre, S.M.: The effect of stratification on the surface resistance for very rough vegetated and urban surfaces. In: 6th International Conference on Urban Climate, June 12–16, Goteborg, Sweden, ISBN-10:91-613-9000-1, pp. 415–418, 2006 (submitted to Bound.-Layer Meteorol.).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • C.S.B. Grimmond
    • 1
    Email author
  • Martin Best
    • 2
  • Janet Barlow
    • 3
  • A. J. Arnfield
    • 4
  • J.-J. Baik
    • 5
  • A. Baklanov
    • 6
  • S. Belcher
    • 3
  • M. Bruse
    • 7
  • I. Calmet
    • 8
  • F. Chen
    • 9
  • P. Clark
    • 10
  • A. Dandou
    • 11
  • E. Erell
    • 12
  • K. Fortuniak
    • 13
  • R. Hamdi
    • 14
  • M. Kanda
    • 15
  • T. Kawai
    • 15
  • H. Kondo
    • 16
  • S. Krayenhoff
    • 17
  • S. H. Lee
    • 18
  • S.-B. Limor
    • 19
  • A. Martilli
    • 20
  • V. Masson
    • 21
  • S. Miao
    • 22
  • G. Mills
    • 23
  • R. Moriwaki
    • 24
  • K. Oleson
    • 25
  • A. Porson
    • 26
  • U. Sievers
    • 27
  • M. Tombrou
    • 11
  • J. Voogt
    • 28
  • T. Williamson
    • 29
  1. 1.King’s College LondonLondonUK
  2. 2.Met Office, Hadley Centre for Climate Prediction and ResearchBracknellUK
  3. 3.Department of MeteorologyUniversity of ReadingReadingUK
  4. 4.Department of GeographyThe Ohio State UniversityColumbusUSA
  5. 5.School of Earth and Environmental SciencesSeoul National UniversitySeoulKorea
  6. 6.Danish Meteorological InstituteDMICopenhagenDenmark
  7. 7.Institute of GeographyJohannes-Gutenberg University of MainzMainzGermany
  8. 8.Laboratoire de Mécanique des Fluides, Ecole Centrale de Nantes (ECN)UMR 6598 CNRSNantes Cedex 3France
  9. 9.Research Applications LaboratoryNational Center for Atmospheric Research (NCAR)BoulderUSA
  10. 10.Met Office, Joint Centre for Mesoscale Meteorology (JCMM)ReadingUK
  11. 11.Department of Environmental Physics and MeteorologyNational and Kapodistrian University of AthensAthensGreece
  12. 12.Jacob Blaustein Institute for Desert Research, Sede-Boqer Campus MidreshetBen Gurion University of the NegevBen-GurionIsrael
  13. 13.Department of Meteorology and ClimatologyUniversity of LodzLodzPoland
  14. 14.Royal Meteorological InstituteBrusselsBelgium
  15. 15.Tokyo Institute of TechnologyTokyoJapan
  16. 16.National Institute of Advanced Industrial Science and TechnologyIbarakiJapan
  17. 17.Department of GeographyUniversity of British ColumbiaVancouverCanada
  18. 18.School of Earth and Environmental SciencesSeoul National UniversitySeoulKorea
  19. 19.Ben-Gurion University of the NegevBeer-ShevaIsrael
  20. 20.Centro de Investigaciones EnergéticasMedioambientales y Tecnológicas (CIEMAT)MadridSpain
  21. 21.Centre National de Recherches. Météorologiques, Meteo-FranceToulouse CedexFrance
  22. 22.Institute of Urban MeteorologyBeijingP.R. China
  23. 23.School of Geography, Planning & Environmental PolicyUniversity CollegeDublin 4Ireland
  24. 24.Department of Civil EngineeringTokyo Institute of TechnologyTokyoJapan
  25. 25.National Center for Atmospheric Research (NCAR)BoulderUSA
  26. 26.Department of MeteorologyUniversity of ReadingReadingUK
  27. 27.Deutscher WetterdienstFreiburgGermany
  28. 28.Department of GeographyUniversity of Western OntarioLondonCanada
  29. 29.University of AdelaideAdelaideAustralia

Personalised recommendations