Spatio-Temporal Analysis of Urban Heatwaves Using Tukey g-and-h Random Field Models

Daisuke Murakami, Gareth W. Peters, Tomoko Matsui, Yoshiki Yamagata

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Real-time heatwave risk management with fine-grained spatial resolution is important for analysis of urban heat island (UHI) effects and local heatwaves. This study analyzed the spatio-temporal behavior of ground temperatures and developed methods for modeling them. The developed models consider two higher-order stochastic spatial properties (skewness and kurtosis), which are key to understanding and describing local temperature fluctuations and UHI effects. Application of the developed models to the greater Tokyo metropolitan area demonstrated the feasibility of statistically incorporating a variety of real datasets. Remotely sensed imagery and data from a variety of ground-based monitoring sites were used to build models linking urban covariates to air temperature. Air temperature models were used to capture high-resolution spatial emulator outputs for modeling ground surface temperatures. The main processes studied were the Tukey g-and-h processes for capturing spatial and temporal aspects of heat processes in urban environments. The main finding is that consideration of not only the mean temperature but also the variance, skewness, and kurtosis parameters can reveal hidden heatwave structures.

Original languageEnglish
Article number9153778
Pages (from-to)79869-79888
Number of pages20
JournalIEEE Access
Publication statusPublished - 2021
Externally publishedYes


  • Heatwave
  • ground temperature modeling
  • local approximate Gaussian process
  • remote sensing
  • spatial statistics

ASJC Scopus subject areas

  • General Computer Science
  • General Materials Science
  • General Engineering


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