Spatiotemporal Analysis of Urban Heatwaves Using Tukey G-and-H Random Field Models

41 Pages Posted: 8 May 2020

See all articles by Daisuke Murakami

Daisuke Murakami

University of Tsukuba - Graduate School of Systems and Information Engineering

Gareth Peters

Department of Actuarial Mathematics and Statistics, Heriot-Watt University; University College London - Department of Statistical Science; University of Oxford - Oxford-Man Institute of Quantitative Finance; London School of Economics & Political Science (LSE) - Systemic Risk Centre; University of New South Wales (UNSW) - Faculty of Science

Tomoko Matsui

Independent

Date Written: April 14, 2020

Abstract

The statistical quantification of temperature processes for the analysis of urban heat island (UHI) effects and local heat-waves is an increasingly important application domain in smart city dynamic modelling. This leads to the increased importance of real-time heatwave risk management on a fine-grained spatial resolution. This study attempts to analyze and develop new methods for modelling the spatio-temporal behavior of ground temperatures. The developed models consider higher-order stochastic spatial properties such as skewness and kurtosis, which are key components for understanding and describing local temperature fluctuations and UHI's. The developed models are applied to the greater Tokyo metropolitan area for a detailed real-world data case study. The analysis also demonstrates how to statistically incorporate a variety of real datasets. This includes remote sensed imagery and a variety of ground based monitoring site data to build models linking city and urban co-variates to air temperature. The air temperature models are then used to capture high resolution spatial emulator outputs for ground surface temperature modelling. The main class of processes studied include the Tukey g-and-h processes for capturing spatial and temporal aspects of heat processes in urban environments.

Suggested Citation

Murakami, Daisuke and Peters, Gareth and Matsui, Tomoko, Spatiotemporal Analysis of Urban Heatwaves Using Tukey G-and-H Random Field Models (April 14, 2020). Available at SSRN: https://ssrn.com/abstract=3575789 or http://dx.doi.org/10.2139/ssrn.3575789

Daisuke Murakami

University of Tsukuba - Graduate School of Systems and Information Engineering ( email )

Ibaraki, 305-8573
Japan

Gareth Peters (Contact Author)

Department of Actuarial Mathematics and Statistics, Heriot-Watt University ( email )

Edinburgh Campus
Edinburgh, EH14 4AS
United Kingdom

HOME PAGE: http://garethpeters78.wixsite.com/garethwpeters

University College London - Department of Statistical Science ( email )

1-19 Torrington Place
London, WC1 7HB
United Kingdom

University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )

University of Oxford Eagle House
Walton Well Road
Oxford, OX2 6ED
United Kingdom

London School of Economics & Political Science (LSE) - Systemic Risk Centre ( email )

Houghton St
London
United Kingdom

University of New South Wales (UNSW) - Faculty of Science ( email )

Australia

Tomoko Matsui

Independent ( email )

Here is the Coronavirus
related research on SSRN

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