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© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  29 Oct 2020

29 Oct 2020

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This preprint is currently under review for the journal ACP.

Modelling spatiotemporal variations of the canopy layer urban heat island in Beijing at the neighbourhood-scale

Michael Biggart1, Jenny Stocker2, Ruth M. Doherty1, Oliver Wild3, David Carruthers2, Sue Grimmond4, Yiqun Han5,6, Pingqing Fu7,8, and Simone Kotthaus4,9 Michael Biggart et al.
  • 1School of Geosciences, The University of Edinburgh, Edinburgh, UK
  • 2Cambridge Environmental Research Consultants, Cambridge, UK
  • 3Lancaster Environment Centre, Lancaster University, Lancaster, UK
  • 4Department of Meteorology, University of Reading, Reading, UK
  • 5State Key Joint Laboratory for Environmental Simulation and Pollution Control, College of Environment Sciences and Engineering, Peking University, Beijing, China
  • 6Environmental Research Group, MRC Centre for Environment and Health, King’s College London, London, UK
  • 7Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • 8Institute of Surface-Earth System Science, Tianjin University, Tianjin, China
  • 9Institut Pierre Simon Laplace, École Polytechnique, Palaiseau, France

Abstract. Information on the spatiotemporal characteristics of Beijing's urban-rural near-surface air temperature difference, known as the canopy layer urban heat island (UHI), is important for future urban climate management strategies. This paper investigates the variation of near-surface air temperatures within Beijing at a neighbourhood-scale resolution (~ 100 m) during winter 2016 and summer 2017. We perform simulations using the urban climate component of the ADMS-Urban model with land surface parameters derived from both Local Climate Zone classifications and OpenStreetMap land use information. Through sensitivity simulations, the relative impacts of surface properties and anthropogenic heat emissions on the temporal variation of Beijing's UHI are quantified. Measured UHI intensities between central Beijing (Institute of Atmospheric Physics) and a rural site (Pinggu) during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) campaigns, peak during the evening at ~ 4.5 °C in both seasons. In winter, the nocturnal UHI is dominated by anthropogenic heat emissions but is underestimated by the model. Higher resolution anthropogenic heat emissions may capture the effects of local sources (e.g. residential buildings and adjacent major roads). In summer, evening UHI intensities are underestimated, especially during heatwaves. The inability to fully replicate the prolonged release of heat stored in the urban fabric may explain this. Observed negative daytime UHI intensities in summer are more successfully captured when surface moisture levels in central Beijing are increased. However, the spatial correlation between simulated air temperatures and satellite-derived land surface temperatures is stronger with a lower urban moisture scenario. This result suggests that near-surface air temperatures at the urban meteorological site are likely influenced by fine-scale green spaces that are unresolved by the available land cover data and demonstrates the expected differences between surface and air temperatures related to canopy layer advection. This study lays the foundations for future studies of heat-related health risks and UHI mitigation strategies across Beijing and other megacities.

Michael Biggart et al.

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Michael Biggart et al.

Michael Biggart et al.


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Publications Copernicus
Short summary
Heat-related illnesses are of increasing concern in China given its rapid urbanisation and our ever-warming climate. We examine the relative impacts that land surface properties and anthropogenic heat have on the urban heat island (UHI) in Beijing using ADMS-Urban. Air temperature measurements and satellite-derived land surface temperatures provide valuable means of evaluating modelled spatiotemporal variations. This work provides critical information for urban planners and UHI mitigation.
Heat-related illnesses are of increasing concern in China given its rapid urbanisation and our...