Skip to main content
Log in

Normalized urban heat island (UHI) indicators: Classifying the temporal variation of UHI for building energy simulation (BES) applications

  • Research Article
  • Advances in Modeling and Simulation Tools
  • Published:
Building Simulation Aims and scope Submit manuscript

Abstract

Despite known effects of urban heat island (UHI) on building energy consumption such as increased cooling energy demand, typical building energy simulation (BES) practices lack a standardized approach to incorporate UHI into building energy predictions. The seasonal and diurnal variation of UHI makes the task of incorporating UHI into BES an especially challenging task, often limited by the availability of detailed hourly temperature data at building location. This paper addresses the temporal variation of UHI by deriving four normalized UHI indicators that can successfully capture the seasonal and diurnal variation of UHI. The accuracy of these indicators was established across four climate types including hot and humid (Miami, FL), hot and dry (Los Angeles, CA), cold and dry (Denver, CO), and cold and humid (Chicago, IL), and three building types including office, hospital, and apartments. These four indicators are mean summer daytime UHI, mean summer nighttime UHI, mean winter daytime UHI, and mean winter nighttime UHI, which can accurately predict cooling, heating, and annual energy consumption with mean relative error of less than 1%. Not only do these indicators simplify the application of UHI to BES but also, they provide a new paradigm for UHI data collection, storage, and usage, specifically for the purpose of BES.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Bernard J, Musy M, Calmet I, et al. (2017). Urban heat island temporal and spatial variations: Empirical modeling from geographical and meteorological data. Building and Environment, 125: 423–438.

    Article  Google Scholar 

  • Callen HB (1985). Thermodynamics and an Introduction to Thermostatistics, 2nd edn. New York: John Wiley & Sons.

    MATH  Google Scholar 

  • Deru M, Field K, Studer D, et al. (2011). U.S. Department of Energy Commercial Reference Building Models of the National Building Stock. Available at https://digitalscholarship.unlv.edu/renew_pubs/44. Accessed 1 Mar 2022.

  • Gao Z, Hou Y, Chen W (2019). Enhanced sensitivity of the urban heat island effect to summer temperatures induced by urban expansion. Environmental Research Letters, 14: 094005.

    Article  Google Scholar 

  • Gracik S, Heidarinejad M, Liu J, et al. (2015). Effect of urban neighborhoods on the performance of building cooling systems. Building and Environment, 90: 15–29.

    Article  Google Scholar 

  • Guattari C, Evangelisti L, Balaras CA (2018). On the assessment of urban heat island phenomenon and its effects on building energy performance: A case study of Rome (Italy). Energy and Buildings, 158: 605–615.

    Article  Google Scholar 

  • Hassid S, Santamouris M, Papanikolaou N, et al. (2000). The effect of the Athens heat island on air conditioning load. Energy and Buildings, 32: 131–141.

    Article  Google Scholar 

  • Huang K, Li X, Liu X, et al. (2019). Projecting global urban land expansion and heat island intensification through 2050. Environmental Research Letters, 14: 114037.

    Article  Google Scholar 

  • Khalil U, Aslam B, Azam U, et al. (2021). Time series analysis of land surface temperature and drivers of urban heat island effect based on remotely sensed data to develop a prediction model. Applied Artificial Intelligence, 35: 1803–1828.

    Article  Google Scholar 

  • Li C, Zhou J, Cao Y, et al. (2014). Interaction between urban microclimate and electric air-conditioning energy consumption during high temperature season. Applied Energy, 117: 149–156.

    Article  Google Scholar 

  • Li H, Wolter M, Wang X, et al. (2018). Impact of land cover data on the simulation of urban heat island for Berlin using WRF coupled with bulk approach of Noah-LSM. Theoretical and Applied Climatology, 134: 67–81.

    Article  Google Scholar 

  • Li X, Zhou Y, Yu S, et al. (2019). Urban heat island impacts on building energy consumption: A review of approaches and findings. Energy, 174: 407–419.

    Article  Google Scholar 

  • Martin-Vide J, Sarricolea P, Moreno-Garc MC (2015). On the definition of urban heat island intensity: The “rural” reference. Frontiers in Earth Science, 3: 24.

    Article  Google Scholar 

  • Mirzaei PA (2015). Recent challenges in modeling of urban heat island. Sustainable Cities and Society, 19: 200–206.

    Article  Google Scholar 

  • Mustafa EK, Co Y, Liu G, et al. (2020). Study for predicting land surface temperature (LST) using landsat data: a comparison of four algorithms. Advances in Civil Engineering, 2020: 7363546.

    Article  Google Scholar 

  • Ramakreshnan L, Aghamohammadi N, Fong CS, et al. (2019). Empirical study on temporal variations of canopy-level Urban Heat Island effect in the tropical city of Greater Kuala Lumpur. Sustainable Cities and Society, 44: 748–762.

    Article  Google Scholar 

  • Sangiorgio V, Fiorito F, Santamouris M (2020). Development of a holistic urban heat island evaluation methodology. Scientific Reports, 10: 17913.

    Article  Google Scholar 

  • Santamouris M (2020). Recent progress on urban overheating and heat island research. Integrated assessment of the energy, environmental, vulnerability and health impact. Synergies with the global climate change. Energy and Buildings, 207: 109482.

    Article  Google Scholar 

  • Singh M, Sharston R (2022). Quantifying the dualistic nature of urban heat Island effect (UHI) on building energy consumption. Energy and Buildings, 255: 111649.

    Article  Google Scholar 

  • Street M, Reinhart C, Norford L, et al. (2013). Urban heat island in Boston: An evaluation of urban air-temperature models for predicting building energy use. In: Proceedings of the 13th International IBPSA Building Simulation Conference, Chambéry, France.

  • Szymanowski M, Kryza M (2012). Local regression models for spatial interpolation of urban heat island—an example from Wrocław, SW Poland. Theoretical and Applied Climatology, 108: 53–71.

    Article  Google Scholar 

  • UCAR/NCAR (2015). UrbaNet Mesonet Data. Version 1.0. UCAR/NCAR—Earth Observing Laboratory. NOAA/Earth System Research Laboratory. Available at https://data.eol.ucar.edu/dataset/100.024. Accessed 05 Aug 2021.

  • Ulpiani G (2021). On the linkage between urban heat island and urban pollution island: Three-decade literature review towards a conceptual framework. Science of the Total Environment, 751: 141727.

    Article  Google Scholar 

  • USDOE (2022). Commercial prototype building models. U.S. Department of Energy. Available at https://www.energycodes.gov/prototype-building-models#Commercial. Accesed 24 March 2022.

  • Vaidyanathan A, Malilay J, Schramm P, et al. (2020). Heat-related deaths—United States, 2004–2018. MMWR Morbidity and Mortality Weekly Report, 69: 729–734.

    Article  Google Scholar 

  • Wang L, Hou H, Weng J (2020). Ordinary least squares modelling of urban heat island intensity based on landscape composition and configuration: A comparative study among three megacities along the Yangtze River. Sustainable Cities and Society, 62: 102381.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

Both authors contributed to the study conception and design. Building energy simulations and data analysis was conducted by Manan Singh, in addition to writing the first draft. Ryan Sharston provided guidance on the study design and methodology, as well as contributed to revising and preparing the manuscript for publication.

Corresponding author

Correspondence to Manan Singh.

Ethics declarations

The authors have no competing interests to declare that are relevant to the content of this article.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Singh, M., Sharston, R. Normalized urban heat island (UHI) indicators: Classifying the temporal variation of UHI for building energy simulation (BES) applications. Build. Simul. 16, 1645–1658 (2023). https://doi.org/10.1007/s12273-023-1048-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12273-023-1048-7

Keywords

Navigation