Investigation of the impact of anthropogenic heat flux within an urban land surface model and PILPS-urban
Results from the first international urban model comparison experiment (PILPS-Urban) suggested that models which neglected the anthropogenic heat flux within the surface energy balance performed at least as well as models that include the source term, but this could not be explained. The analyses undertaken show that the results from PILPS-Urban were masked by the signal from including vegetation, which was identified in PILPS-Urban as being important. Including the anthropogenic heat flux does give improved performance, but the benefit is small for the site studied given the relatively small magnitude of this flux relative to other terms in the surface energy balance. However, there is no further benefit from including temporal variations in the flux at this site. The importance is expected to increase at sites with a larger anthropogenic heat flux and greater temporal variations.
KeywordsAnthropogenic heat JULES Surface energy balance Urban environment
M. Best was supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (CA01101). Grimmond acknowledges support from Newton Fund/Met Office CSSP-China. Funds to support PILPS-Urban were provided by the Met Office (P001550). We would like to thank Andrew Coutts, Jason Beringer and Nigell Tapper for allowing their data to be used for the comparison. We would also like to thank Maggie Hendry and Mariana Gouvea for undertaking the JULES simulations for PILPS-Urban and everyone else who contributed model simulations to the comparison.
- Best MJ, Pryor M, Clark DB, Rooney GG, Essery RHL, 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
- Cullen MJP (1993) The unified forecast/climate model. Meteorol Mag 122:81–94Google Scholar
- Grimmond CSB (1992) The subruban energy balance: Methodological considerations and results for a mid-latitude west coast city under winter and spring conditions. Int J Climatol 12:481–497Google Scholar
- 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
- 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 G-J, Trombou M, Voogt J, Young D, 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
- Hallenbeck M, Rice M, Smith B, Cornell-Martinez C, Wilkinson J (1997) Vehicle volume distribution by classification. Washington State Transportation Center, University of Washington, 54 pp. [Available from Washington State Transportation Center, University of Washington, 1107 NE 45th St. Suite 535, Seattle WA 98105]Google Scholar
- Hamdi R, Degrauwe D, Duerinckx A, Cedilnik J, Costa V, Dalkilic T, Essaouini K, Jerczynki M, Kocaman F, Kullmann L, Mahfouf J-F, Meier F, Sassi M, Schneider S, Váňa F, Termonia P (2014) Evaluating the performance of SURFEXv5 as a new land surface scheme for the ALADINcy36 and ALARO-0 models. Geosci Model Dev 7:23–39. doi: 10.5194/gmd-7-23-2014 CrossRefGoogle Scholar
- Kotthaus S, Grimmond CSB (2014) Energy exchange in a dense urban environment—part I: temporal variability of long-term observations in central London. Urban Climate. doi: 10.1016/j.uclim.2013.10.002
- Masson V (2000) A physically-based scheme for the urban energy budget in atmospheric models. Bound-Layer Meteorol 41:1011–1026Google Scholar
- McCarthy MP, Best MJ, Betts RA (2010) Climate change in cities due to global warming and urban effects. Geophys Res Letters 37: L09705. doi: 10.1029/2010GL042845
- Oleson KW, Bonan GB, Feddema J, Vertenstein M, Grimmond CSB (2008) An urban parameterization for a global climate model: 1. Formulation and Evaluation for two Cities J Appl Meteorol Climatol 47:1038–1060Google Scholar