Estimating anthropogenic heat flux by assimilating meteorological observations with a Kalman filter approach

Anthropogenic heat (AH) emissions in urban environments alter the surface energy budget and significantly influence urban climates. However, these emissions vary spatiotemporally, leading to considerable uncertainty in their estimation. As remote sensing in the urban environment advances, the remotely sensed urban surface temperatures are becoming increasingly available. Yet, assimilating these observations into surface energy modelling for AH estimation has not been fully explored. In this study, a model for AH estimation based on the Kalman filter-surface energy balance (KF-SEB) is developed. Urban meteorological data, including air temperature and building surface temperature, are assimilated into the Kalman filter (KF), yielding sensible heat flux, building heat storage and estimated AH using the surface energy balance (SEB) equation. The KF-SEB model is evaluated using two forward models with predefined AH emissions. The first model is a simple slab model, and the second one is a more complex single-layer urban canopy model (UCM). The results show that the KF-SEB model accurately captures the magnitude and temporal variation of AH, with reduced uncertainties compared to previous studies. This study offers a novel approach to AH estimation based on urban meteorological data and provides important insights into the feedback between urban microclimates and anthropogenic energy use. This article is part of the theme issue ‘Urban heat spreading above and below ground’.