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 LandScan^TM 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.

数值天气预报模型逐渐被用来以提高空间分辨率来缩小城市未来的气候。代表快速增长的城市地区的边界条件对于更合理的未来预测至关重要。在这项工作中，构建了当前和未来的 1 公里全球人为热排放 (AHE) 数据集。为了改进现有的 AHE 地图，将 30 角秒 VIIRS 卫星图像输出（例如夜间灯光和夜间火灾）与 LandScan ^TM人口数据集合并在一起。还开发了 AHE 的未来场景，同时考虑了辐射强迫路径（即代表性浓度路径）、社会条件路径（即共享社会经济路径）、未来 1 公里城市化概率图以及估计变化的模型。人口分布。新数据集突出了两个不同的特征： (1) 与其他最近的数据集相比，AHE 的空间异质性更强，(2) 在未来的 AHE 地图中考虑了未来的城市扩张和气候变化。在最坏的情况下，多个城市的预计 AHE 显着增加，增强了对未来 AHE 进行进一步评估的必要性。