Abstract
Numerical weather prediction models are progressively used to downscale future climate in cities at increasing spatial resolutions. Boundary conditions representing rapidly growing urban areas are imperative to more plausible future predictions. In this work, 1-km global anthropogenic heat emission (AHE) datasets of the present and future are constructed. To improve present AHE maps, 30 arc-second VIIRS satellite imagery outputs such as nighttime lights and night-fires were incorporated along with the LandScanTM population dataset. A futuristic scenario of AHE was also developed while considering pathways of radiative forcing (i.e. representative concentration pathways), pathways of social conditions (i.e. shared socio-economic pathways), a 1-km future urbanization probability map, and a model to estimate changes in population distribution. The new dataset highlights two distinct features; (1) a more spatially-heterogeneous representation of AHE is captured compared with other recent datasets, and (2) consideration of future urban sprawls and climate change in futuristic AHE maps. Significant increases in projected AHE for multiple cities under a worst-case scenario strengthen the need for further assessment of futuristic AHE.
Highlights
Numerical weather prediction models are progressively used to downscale future climate in cities at increasing spatial resolutions
Among the factors contributing to the aforesaid risks is anthropogenic heating which is human-induced heat emitted into the atmosphere
Futuristic anthropogenic heat emission (AHE) maps that are in line with a city or country’s plausible response to climate change are lacking and are limited to annual or monthly values; 3
Summary
68% of the global population is predicted to be urban-dwellers by the year 20501. The rate of urbanization, commonly estimated in terms of urban population growth, differs by region with most developing nations increasing faster than developed ones. Robust, and freely accessible datasets were used as inputs These datasets correspond to country-level energy consumption data, digital maps, satellite images, urban growing models, and climate model outputs which are operationally maintained to improve its accuracy and performance. Population maps such as LandScanTM 11 contain spatial information of population with 30 arc-second resolutions and is freely available for non-commercial use. Combining a scenario with the datasets mentioned earlier, a global urban sprawl dataset, and a population growth model, future AHE (2050 s scenario defined by RCP8.5 and SSP3) map was constructed. The simple model presented can be used to construct other future AHE scenarios
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