Influence of ground surface characteristics on the mean radiant temperature in urban areas
- 647 Downloads
The effect of variations in land cover on mean radiant temperature (T mrt ) is explored through a simple scheme developed within the radiation model SOLWEIG. Outgoing longwave radiation is parameterised using surface temperature observations on a grass and an asphalt surface, whereas outgoing shortwave radiation is modelled through variations in albedo for the different surfaces. The influence of ground surface materials on T mrt is small compared to the effects of shadowing. Nevertheless, altering ground surface materials could contribute to a reduction in T mrt to reduce the radiant load during heat-wave episodes in locations where shadowing is not an option. Evaluation of the new scheme suggests that despite its simplicity it can simulate the outgoing fluxes well, especially during sunny conditions. However, it underestimates at night and in shadowed locations. One grass surface used to develop the parameterisation, with very different characteristics compared to an evaluation grass site, caused T mrt to be underestimated. The implications of using high temporal resolution (e.g. 15 minutes) meteorological forcing data under partly cloudy conditions are demonstrated even for fairly proximal sites.
KeywordsSOLWEIG Surface temperature Gothenburg London
This work is financially supported by FORMAS – the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning, H2020-EO-1-2014 Project 637519: URBANFLUXES and Newton Fund/Met Office Climate Services CSSP - China. Many thanks to William Morrison and the many others at University of Reading who maintain LUMA data collection, Barbican Estate and City of London Girls School for providing the data.
Open image in new window URBANFLUXES is co-financed by "HORIZON 2020" EU Framework Programme.
- Andersson-Sköld Y, Thorsson S, Rayner D, Lindberg F, Janhäll S, Jonsson A, Moback U, Bergman R, Granberg M (2015) An integrated method for assessing climate-related risks and adaptation alternatives in urban areas. Climate Risk Manag 7:31–50Google Scholar
- Chen Y-C, Lin T-P, Matzarakis A (2014) Comparison of mean radiant temperature from field experiment and modelling: a case study in Freiburg, Germany. Theor Appl Climatol 118:535–551Google Scholar
- Cluis DA (1972) Relationship between stream water temperature and ambient air temperature—a simple autoregressive model for mean daily stream water temperature fluctuations. Nord Hydrol 3:65–71Google Scholar
- Fanger PO (1970) Thermal Comfort-Analysis and Applications in Environmental Engineering. Danish Technical Press, Copenhagen. 256 ppGoogle Scholar
- Holmer B, Lindberg F, Rayner D, Thorsson, S (2015) How to transform the standing man from a box to a cylinder—a modified methodology to calculate mean radiant temperature in field studies and models, ICUC9—9 th International Conference on Urban Climate jointly with AMS 12th Symposium on the Urban Environment, BPH5: Human perception and new indicators. Toulouse, JulyGoogle Scholar
- Höppe P (1992) A new procedure to determine the mean radiant temperature outdoors. Wetter unt Leben 44:147–151Google 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 10(2):262–280Google Scholar
- Lau KK-L, Ren C, Ho J, Ng E (2015) Numerical modelling of mean radiant temperature in high-density sub-tropical urban environment. Energy Build. doi: 10.1016/j.enbuild.2015.06.035
- Lindberg F, Holmer B, Thorsson S, Rayner D (2013) Characteristics of the mean radiant temperature in high latitude cities—implications for sensitive climate planning applications. Int J Biometeorol 58:613–627Google Scholar
- Lindberg F, Grimmond CSB, Onomura S, Järvi L, Ward H (2015b) UMEP—an integrated tool for urban climatology and climate-sensitive planning applications. ICUC9—9 th International Conference on Urban Climate jointly with 12th Symposium on the Urban Environment, TUKUP7 (cont): Warning plans & Decision support tools. Toulouse, July 2015Google Scholar
- Oke T (1987) Boundary layer climates. Routledge, Cambridge, p. 435Google Scholar
- Ordnance Survey (2010) © Crown database right 2010. An Ordnance Survey/EDINA supplied service. [Available online at http://www.ordnancesurvey.co.uk/oswebsite/.]
- QGIS Development Team (2015) QGIS geographic information system. Open Source Geospatial Foundation Project. http://qgis.osgeo.org
- Ratti CF, Richens P (1999) Urban texture analysis with image processing techniques. Proc CAADFutures99, Atalanta, GAGoogle Scholar
- VDI (1998) Methods for the human-biometeorological assessment of climate and air hygiene for urban and regional planning. Part I: climate. VDI 3787, Part 2, Belin 29pGoogle Scholar