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

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 ground temperatures developed methods modeling them. The models consider two higher-order stochastic properties (skewness kurtosis), which are key to understanding describing temperature fluctuations UHI effects. Application greater Tokyo metropolitan area demonstrated feasibility statistically incorporating a variety real datasets. Remotely sensed imagery data from ground-based monitoring sites were used build linking covariates air temperature. Air capture high-resolution emulator outputs surface temperatures. main processes studied Tukey g-and-h capturing temporal aspects in environments. finding that consideration not only mean but also variance, skewness, kurtosis parameters can reveal hidden structures.