Boundary-Layer Meteorology

, Volume 146, Issue 3, pp 421–446 | Cite as

Analysis of the Seasonal Cycle Within the First International Urban Land-Surface Model Comparison

  • M. J. Best
  • C. S. B. Grimmond


A number of urban land-surface models have been developed in recent years to satisfy the growing requirements for urban weather and climate interactions and prediction. These models vary considerably in their complexity and the processes that they represent. Although the models have been evaluated, the observational datasets have typically been of short duration and so are not suitable to assess the performance over the seasonal cycle. The First International Urban Land-Surface Model comparison used an observational dataset that spanned a period greater than a year, which enables an analysis over the seasonal cycle, whilst the variety of models that took part in the comparison allows the analysis to include a full range of model complexity. The results show that, in general, urban models do capture the seasonal cycle for each of the surface fluxes, but have larger errors in the summer months than in the winter. The net all-wave radiation has the smallest errors at all times of the year but with a negative bias. The latent heat flux and the net storage heat flux are also underestimated, whereas the sensible heat flux generally has a positive bias throughout the seasonal cycle. A representation of vegetation is a necessary, but not sufficient, condition for modelling the latent heat flux and associated sensible heat flux at all times of the year. Models that include a temporal variation in anthropogenic heat flux show some increased skill in the sensible heat flux at night during the winter, although their daytime values are consistently overestimated at all times of the year. Models that use the net all-wave radiation to determine the net storage heat flux have the best agreement with observed values of this flux during the daytime in summer, but perform worse during the winter months. The latter could result from a bias of summer periods in the observational datasets used to derive the relations with net all-wave radiation. Apart from these models, all of the other model categories considered in the analysis result in a mean net storage heat flux that is close to zero throughout the seasonal cycle, which is not seen in the observations. Models with a simple treatment of the physical processes generally perform at least as well as models with greater complexity.


Model complexity Seasonal cycle Urban model comparison Vegetation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Supplementary material

10546_2012_9769_MOESM1_ESM.doc (5.6 mb)
ESM 1 (DOC 5,709 kb)


  1. Allen L, Lindberg F, Grimmond CSB (2011) Global to city scale urban anthropogenic heat flux: model and variability. Int J Climatol 31: 1990–2005. doi: 10.1002/joc.2210 CrossRefGoogle Scholar
  2. Anandakumar K (1999) A study on the partition of net radiation into heat fluxes on a dry asphalt surface. Atmos Environ 33: 3911–3918CrossRefGoogle Scholar
  3. Avissar R, Pielke RA (1989) A parameterization of heterogeneous land surfaces for atmospheric numerical models and its impact on regional meteorology. Mon Weather Rev 117: 2113–2136CrossRefGoogle Scholar
  4. Best MJ (2005) Representing urban areas within operational numerical weather prediction models. Boundary-Layer Meteorol 114: 91–109CrossRefGoogle Scholar
  5. Best MJ (2006) Progress towards better weather forecasts for city dwellers: From short range to climate change. Theor Appl Climatol 84: 47–55CrossRefGoogle Scholar
  6. Best MJ, Grimmond CSB, Villani MG (2006) Evaluation of the urban tile in MOSES using surface energy balance observations. Boundary- Layer Meteorol 118: 503–525CrossRefGoogle Scholar
  7. Best MJ, Pryor M, Clark DB, Rooney GG, Essery RLH, Ménard CB, Edwards JM, Hendry MA, Porson A, Gedney N, Mercado LM, Sitch S, Blyth E, Boucher O, Cox PM, Grimmond CSB, Harding RJ (2011) The Joint UK Land Environment Simulator (JULES), Model description – Part 1: Energy and water fluxes. Geosci Model Dev 4: 677–699CrossRefGoogle Scholar
  8. Chen F, Kusaka H, Tewari M, Bao J, Hirakuchi H (2004) Utilizing the coupled WRF/LSM/Urban modeling system with detailed urban classification to simulate the urban heat island phenomena over the Greater Houston area. In: Fifth symposium on the urban environment, CD-ROM. 9.11. American Meteorological Society, Vancouver, BCGoogle Scholar
  9. Coutts AM, Beringer J, Tapper NJ (2007a) Characteristics influencing the variability of urban CO2 fluxes in Melbourne, Australia. Atmos Environ 41: 51–62CrossRefGoogle Scholar
  10. Coutts AM, Beringer J, Tapper NJ (2007b) Impact of increasing urban density on local climate: spatial and temporal variations in the surface energy balance in Melbourne, Australia. J Appl Meteorol 47: 477–493Google Scholar
  11. Dandou A, Tombrou M, Akylas E, Soulakellis N, Bossioli E (2005) Development and evaluation of an urban parameterization scheme in the Penn State/NCAR Mesoscale model (MM5). J Geophys Res 110: D10102. doi: 10.1029/2004JD005192 CrossRefGoogle Scholar
  12. Dirmeyer PA, Gao X, Zhao M, Zhichong G, Oki T, Hanasaki N (2006) GSWP-2 multimodel analysis and implications for our perception of the land surface. Bull Am Meteorol Soc 87: 1381–1397CrossRefGoogle Scholar
  13. Dupont S, Mestayer PG (2006) Parameterisation of the urban energy budget with the submesoscale soil model. J Appl Meteorol Climatol 45: 1744–1765CrossRefGoogle Scholar
  14. Dupont S, Mestayer PG, Guilloteau E, Berthier E, Andrieu H (2006) Parameterisation of the urban water budget with the submesoscale soil model. J Appl Meteorol Climatol 45: 624–648CrossRefGoogle Scholar
  15. Essery RLH, Best MJ, Betts RA, Cox PM, Taylor CM (2003) Explicit representation of subgrid heterogeneity in a GCM land surface scheme. J Hydrometeorol 4: 530–543CrossRefGoogle Scholar
  16. Fortuniak K (2003) A slab surface energy balance model (SUEB) and its application to the study on the role of roughness length in forming an urban heat island. Acta Universitatis Wratislaviensis 2542: 368–377Google Scholar
  17. Fortuniak K, Offerle B, Grimmond CSB (2004) Slab surface energy balance scheme and its application to parameterisation of the energy fluxes on urban areas. NATO ASI, Kiev, Ukraine, pp 82–83. Last accessed 4–15 May 2010
  18. Fortuniak K, Offerle B, Grimmond CSB (2005) Application of a slab surface energy balance model to determine surface parameters for urban areas. Lund Electron Rep Phys Geogr 5: 90–91Google Scholar
  19. Grimmond CSB, Souch C, Hubble MD (1996) Influence of tree cover on summertime surface energy balance fluxes, San Gabriel Valley, Los Angeles. Clim Res 6: 45–57CrossRefGoogle Scholar
  20. Grimmond CSB, Oke TR (2002) Turbulent heat fluxes in urban areas: observations and local-scale urban meteorological parameterization scheme (LUMPS). J Appl Meteorol 41: 792–810CrossRefGoogle Scholar
  21. Grimmond CSB, Salmond JA, Oke TA, Offerle B, Lemonsu A (2004) Flux and turbulence measurements at a densely built-up site in Marseille: heat, mass (water and carbon dioxide), and momentum. J Geophys Res 109: D24101. doi: 10.1029/2004JD004936 CrossRefGoogle Scholar
  22. Grimmond CSB, Blackett M, Best MJ, Barlow J, Baik J-J, Belcher SE, Bohnenstengel SI, Calmet I, Chen F, Dandou A, Fortuniak K, Gouvea ML, Hamdi R, Hendry M, Kawai T, Kawamoto Y, Kondo H, Krayenhoff ES, Lee S-H, Loridan T, Martilli A, Masson V, Miao S, Oleson K, Pigeon G, Porson A, Ryu Y-H, Salamanca F, Shashua-Bar L, Steeneveld G-J, Trombou M, Voogt J, Young D, Zhang N (2010) The international urban energy balance models comparison project: first results from phase 1. J Appl Meteorol Climatol 49: 1268–1292. doi: 10.1175/2010JAMC2354.1 CrossRefGoogle Scholar
  23. Grimmond CSB, Blackett M, Best MJ, Baik J-J, Belcher SE, Beringer J, Bohnenstengel SI, Calmet I, Chen F, Coutts A, Dandou A, Fortuniak K, Gouvea ML, Hamdi R, Hendry M, Kanda M, Kawai T, Kawamoto Y, Kondo H, Krayenhoff ES, Lee S-H, Loridan T, Martilli A, Masson V, Miao S, Oleson K, Ooka R, Pigeon G, Porson A, Ryu Y-H, Salamanca F, Steeneveld GJ, Trombou M, Voogt JA, Young DT, Zhang N (2011) Initial results from phase 2 of the international urban energy balance model comparison. Int J Climatol 30: 244–272. doi: 10.1002/joc.2227 CrossRefGoogle Scholar
  24. Hamdi R, Schayes G (2007) Validation of Martilli’s urban boundary layer scheme with measurements from two mid-latitude European cities. Atmos Chem Phys 7: 4513–4526CrossRefGoogle Scholar
  25. Hamdi R, Masson V (2008) Inclusion of a drag approach in the Town Energy Balance (TEB) scheme: offline 1-D evaluation in a street canyon. J Appl Meteorol Climatol 47: 2627–2644CrossRefGoogle Scholar
  26. Harman IN, Best MJ, Belcher SE (2004a) Radiative exchange in an urban street canyon. Boundary-Layer Meteorol 110: 301–316CrossRefGoogle Scholar
  27. Harman IN, Barlow JF, Belcher SE (2004b) Scalar fluxes from urban street canyons.Part II: model. Boundary-Layer Meteorol 113: 387–410CrossRefGoogle Scholar
  28. Harman IN, Belcher SE (2006) The surface energy balance and boundary layer over urban street canyons. Q J R Meteorol Soc 132: 2749–2768CrossRefGoogle Scholar
  29. Henderson-Sellers A, Yang ZL, Dickenson RE (1993) The project for intercomparison of land-surface parameterization schemes. Bull Am Meteorol Soci 74: 1335–1349CrossRefGoogle Scholar
  30. Henderson-Sellers A, Irannejad P, McGuffie K, Pitman A (2003) Predicting land-surface climates-better skill or moving targets?. Geophys Res Lett 30: 1777. doi: 10.1029/2003GL017387 CrossRefGoogle Scholar
  31. Hollinger DY, Richardson AD (2005) Uncertainty in eddy covariance measurements and its application to physiological models. Tree Physiol 25: 873–885CrossRefGoogle Scholar
  32. Irranejad P, Henderson-Sellers A, Sharmeen S (2003) Importance of land-surface parameterization for latent heat simulation in global atmospheric models. Geophys Res Lett 30: 1904. doi: 10.1029/2003/GL018044 CrossRefGoogle Scholar
  33. Jackson TL, Feddema JJ, Oleson KW, Bonan GB, Bauer JT (2010) Parameterization of urban characteristics for global climate modelling. Ann Assoc Am Geogr 100: 848–865CrossRefGoogle Scholar
  34. Kanda M, Kawai T, Kanega M, Moriwaki R, Narita K, Hagishima A (2005a) A simple energy balance model for regular building arrays. Boundary-Layer Meteorol 116: 423–443CrossRefGoogle Scholar
  35. Kanda M, Kawai T, Nakagawa K (2005b) A simple theoretical radiation scheme for regular building arrays. Boundary-Layer Meteorol 114: 71–90CrossRefGoogle Scholar
  36. Kawai T, Kanda M, Narita K, Hagishima A (2007) Validation of a numerical model for urban energy-exchange using outdoor scalemodel measurements. Int J Climatol 27: 1931–1942CrossRefGoogle Scholar
  37. Kawai T, Ridwan MK, Kanda M (2009) Evaluation of the simple urban energy balance model using 1-yr flux observations at two cities. J Appl Meteorol Climatol 48: 693–715CrossRefGoogle Scholar
  38. Kawamoto Y, Ooka R (2006) Analysis of the radiation field at pedestrian level using a meso-scale meteorological model incorporating the urban canopy model. In: ICUC-6, Göteborg, Sweden, 12–16 June 2006Google Scholar
  39. Kawamoto Y, Ooka R (2009a) Accuracy validation of urban climate analysis model using MM5 incorporating a multi-layer urban canopy model. In: ICUC-7, Yokohama, Japan, 28 June–3 July 2009Google Scholar
  40. Kawamoto Y, Ooka R (2009b) Development of urban climate analysis model using MM5 Part 2—incorporating an urban canopy model to represent the effect of buildings. J Environ Eng (Trans AIJ) 74(642):1009–1018 (in Japanese)Google Scholar
  41. Kondo H, Liu FH (1998) A study on the urban thermal environment obtained through a one-dimensional urban canopy model. J Japan Soc Atmos Environ 33:179–192 (in Japanese)Google Scholar
  42. Kondo H, Genchi Y, Kikegawa Y, Ohashi Y, Yoshikado H, Komiyama H (2005) 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. Boundary-Layer Meteorol 116: 395–421CrossRefGoogle Scholar
  43. Koster RD, Suarez MJ (1992) Modelling the land surface boundary in climate models as a composite of independent vegetation stands. J Geophys Res (Atmos) 97: 2697–2715CrossRefGoogle Scholar
  44. Krayenhoff ES, Voogt JA (2007) A microscale three-dimensional urban energy balance model for studying surface temperatures. Boundary- Layer Meteorol 123: 433–461CrossRefGoogle Scholar
  45. Kusaka H, Kondo H, Kikegawa Y, Kimura F (2001) A simple singlelayer urban canopy model for atmospheric models: comparison with multi-layer and slab models. Boundary-Layer Meteorol 101: 329–358CrossRefGoogle Scholar
  46. Lee S-H, Park S-U (2008) A vegetated urban canopy model for meteorological and environmental modelling. Boundary-Layer Meteorol 126: 73–102CrossRefGoogle Scholar
  47. Lemonsu A, Grimmond CSB, Masson V (2004) Modelling the surface energy balance of an old Mediterranean city core. J Appl Meteorol 43: 312–327CrossRefGoogle Scholar
  48. Loridan T, Grimmond CSB (2011a) Characterisation of energy flux partitioning in urban environments: links with surface seasonal properties. J Appl Meteorol Climatol. doi: 10.1175/JAMC-D-11-038.1
  49. Loridan T, Grimmond CSB (2011b) Multi-site evaluation of an urban land-surface model: intra-urban heterogeneity, seasonality, and parameter complexity requirements. Q J R Meteorol Soc. doi: 10.1002/qj.963
  50. Loridan T, Grimmond CSB, Grossman-Clarke S, Chen F, Tewari M, Manning K, Martilli A, Kusaka H, Best M (2010) Trade-offs and responsiveness of the single-layer urban canopy parameterization in WRF: an offline evaluation using the MOSCEM optimization algorithm and field observations. Q J R Meteorol Soc 136: 997–1019. doi: 10.1002/qj.614 CrossRefGoogle Scholar
  51. Loridan T, Grimmond CSB, Offerle BD, Young DT, Smith T, Jarvi L, Lindberg F (2011) Local-scale urban meteorological parameterization scheme (LUMPS): Longwave radiation parameterization and seasonality-related developments. J Appl Meteorol Climatol 50: 185–202. doi: 10.1175/2010JAMC2474.1 CrossRefGoogle Scholar
  52. Martilli A, Clappier A, Rotach MW (2002) An urban surface exchange parameterisation for mesoscale models. Boundary-Layer Meteorol 104: 261–304CrossRefGoogle Scholar
  53. Masson V (2000) A physically-based scheme for the urban energy budget in atmospheric models. Boundary-Layer Meteorol 41: 1011–1026Google Scholar
  54. Masson V, Grimmond CSB, Oke TR (2002) Evaluation of the Town Energy Balance (TEB) scheme with direct measurements from dry districts in two cities. J Appl Meteorol 41: 1011–1026Google Scholar
  55. Mestayer PG, Durand P, Augustin P, Bastin S, Bonnefond J-M, Béenech B, Campistron B, Coppalle A, Delbarre H, Dousset B, Drobinski P, Druilhet A, Fréjafon E, Grimmond CSB, Groleau D, Irvine M, Kergomard C, Kermadi S, Lagouarde J-P, Lenonsu A., Lohou F, Long N, Masson V, Moppert C, Noilhan J, Offerle B, Oke TR, Pigeon G, Puygrenier V, Roberts S, Rosanti J-M, Saïd F, Salmond J, Talbaut M, Voogt J (2005) The urban boundary-layer field campaign in Marseille (UBL/CLU-ESCOMPTE) : Set-up and first results. Boundary-Layer Meteorol 114: 315–365CrossRefGoogle Scholar
  56. Newton T, Oke TR, Grimmond CSB, Roth M (2007) The suburban energy balance in Miami, Florida. Geogr Ann Ser A 89A: 331–347CrossRefGoogle Scholar
  57. Notaro M, Liu Z, Gallimore RG, Williams JW, Gutzler DS, Collins S (2010) Complex seasonal cycle of ecohydrology in the Southwest United States. J Geophys Res 115: G04034. doi: 10.1029/2010JG001382 CrossRefGoogle Scholar
  58. Offerle B, Grimmond CSB, Oke TR (2003) Parameterization of net allwave radiation for urban areas. J Appl Meteorol 42: 1157–1173CrossRefGoogle Scholar
  59. Offerle B, Jonsson P, Eliasson I, Grimmond CSB (2005) Urban modification of the surface energy balance in the West African Sahel: Ouagadougou, Burkina Faso. J Clim 18: 3983–3995CrossRefGoogle Scholar
  60. Oke TR (2004) Initial guidance to obtain representative meteorological observations at urban sites. Instruments and Observing Methods Report 81, WMO/TD 1250, 51 ppGoogle Scholar
  61. Oke TR, Spronken-Smith A, Jauregui E, Grimmond CSB (1999) The energy balance of central Mexico City during the dry season. Atmos Environ 33: 3919–3930CrossRefGoogle Scholar
  62. Oleson KW, Bonan GB, Feddema J, Vertenstein M, Grimmond CSB (2008a) An urban parameterization for a global climate model: 1. Formulation and evaluation for two cities. J Appl Meteorol Climatol 47: 1038–1060CrossRefGoogle Scholar
  63. Oleson KW, Bonan GB, Feddema J, Vertenstein M (2008b) 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: 1061–1076CrossRefGoogle Scholar
  64. Pigeon G, Moscicki MA, Voogt JA, Masson V (2008b) Simulation of fall and winter surface energy balance over a dense urban area using the TEB scheme. Meteorol Atmos Phys 102: 159–171CrossRefGoogle Scholar
  65. Porson A, Harman IN, Bohnenstengel SI, Belcher SE (2009) How many facets are needed to represent the surface energy balance of an urban area?. Boundary-Layer Meteorol 132: 107–128CrossRefGoogle Scholar
  66. Porson A, Clark PA, Harman IN, Best MJ, Belcher SE (2010) Implementation of a new urban energy budget scheme in the MetUM.Part II. Validation against observations and model intercomparison. Q J R Meteorol Soc 136: 1530–1542CrossRefGoogle Scholar
  67. Ryu Y-H, Baik J-J, Lee S-H (2011) A new single-layer urban canopy model for use in mesoscale atmospheric models. J Appl Meteorol Climatol 50: 1773–1794. doi: 10.1175/2011JAMC2665.1 CrossRefGoogle Scholar
  68. Sailor DJ (2011) A review of methods for estimating anthropogenic heat and moisture emissions in the urban environment. Int J Climatol 31: 189–199CrossRefGoogle Scholar
  69. Sailor DJ, Lu L (2004) A top-down methodology for developing diurnal and seasonal anthropogenic heating profiles for urban areas. Atmos Environ 38: 2737–2748CrossRefGoogle Scholar
  70. Salamanca F, Krayenhoff ES, Martilli A (2009) On the derivation of material thermal properties representative of heterogeneous urban neighbourhoods. J Appl Meteorol Climatol 48: 1725–1732CrossRefGoogle Scholar
  71. Salamanca F, Krpo A, Martilli A, Clappier A (2010) A new building energy model coupled with an urban canopy parameterization for urban climate simulations—part I. Formulation, verification, and sensitivity analysis of the model. Theor Appl Climatol 99: 345–356. doi: 10.1007/s00704-009-0142-9 CrossRefGoogle Scholar
  72. Salamanca F, Martilli A (2010) A new Building Energy Model coupled with an Urban Canopy Parameterization for urban climate simulations—part II. Validation with one dimension off-line simulations. Theor Appl Climatol 99: 345–356CrossRefGoogle Scholar
  73. Voogt JA, Grimmond CSB (2000) Modeling surface sensible heat flux using surface radiative temperatures in a simple urban area. J Appl Meteorol 39: 1679–1699CrossRefGoogle Scholar

Copyright information

© Her Majesty the Queen in Right of United Kingdom 2012

Authors and Affiliations

  1. 1.Met OfficeExeterUK
  2. 2.King’s College London, Department of GeographyLondonUK

Personalised recommendations