Advances in Atmospheric Sciences

, Volume 33, Issue 12, pp 1376–1385 | Cite as

Characterizing the urban temperature trend using seasonal unit root analysis: Hong Kong from 1970 to 2015

  • Wai-Ming To
  • Tat-Wai Yu


This paper explores urban temperature in Hong Kong using long-term time series. In particular, the characterization of the urban temperature trend was investigated using the seasonal unit root analysis of monthly mean air temperature data over the period January 1970 to December 2013. The seasonal unit root test makes it possible to determine the stochastic trend of monthly temperatures using an autoregressive model. The test results showed that mean air temperature has increased by 0.169◦C (10 yr)−1 over the past four decades. The model of monthly temperature obtained from the seasonal unit root analysis was able to explain 95.9% of the variance in the measured monthly data — much higher than the variance explained by the ordinary least-squares model using annual mean air temperature data and other studies alike. The model accurately predicted monthly mean air temperatures between January 2014 and December 2015 with a root-mean-square percentage error of 4.2%. The correlation between the predicted and the measured monthly mean air temperatures was 0.989. By analyzing the monthly air temperatures recorded at an urban site and a rural site, it was found that the urban heat island effect led to the urban site being on average 0.865◦C warmer than the rural site over the past two decades. Besides, the results of correlation analysis showed that the increase in annual mean air temperature was significantly associated with the increase in population, gross domestic product, urban land use, and energy use, with the R2 values ranging from 0.37 to 0.43.


urban temperature trend urban heat island effect seasonal unit root tests long-term time series 


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Copyright information

© Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Wai-Ming To
    • 1
  • Tat-Wai Yu
    • 1
  1. 1.Macao Polytechnic InstituteRua de Luis Gonzaga GomesMacao SARChina

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