In this paper we combine statistical modelling and climate models in order to develop a unified statistical framework for quantifying the Urban Heat Footprint (UHF) effect, thus quantifying the urban warming phenomenon. The UHF quantifies the urban warming at any location in the spatio-temporal domain due to different effects, such as anthropogenic effects and climatic effects. These effects can be controlled and configured by our modelling approach, thus allowing the evaluation of different scenarios of interest. We first provide a definition of UHF followed by definitions of the Anthropogenic Effects (AE) components. Then, based on those definitions, we define the fundamental quantity of UHF spatial-temporal stochastic (random) processes. Next, we propose several metrics for quantifying and summarising the UHF, which are statistical estimators. These provide insightful summaries of the population parameters of the UHF stochastic process, and can be easily calculated in practice. To illustrate how our framework can be used, we utilise a Weather Research and Forecasting (WRF) model, and provide detailed examples of various UHF metrics, based on real data of Singapore.
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Nevat, I., Mughal, M.O., Li, X. et al. The Urban Heat Footprint (UHF)—a new unified climatic and statistical framework for urban warming. Theor Appl Climatol (2020). https://doi.org/10.1007/s00704-019-03044-y
- Urban Heat Footprint (UHF)
- Anthropogenic effects
- Climate model