The rising temperature makes the weather becoming more extreme. Understanding how extreme hot temperature-heat wave events (HWEs)-are likely to alter individual heat exposure and sensitivity is crucial for developing climate change mitigation and adaptation strategies. Despite the importance, little is known about the real-time impacts of HWEs on individual daily life in developing nations, like China. To fill this gap, we adopt over 1544 thousand Weibo (Chinese Twitter) social media data, coupled with meteorological conditions people face when posting, to assess the heat exposure and people's sensitivity to HWEs across 31 mega-cities in China. The results show the hotspot of Weibo heat is coincident with the extremely hot temperature, with a correlation of 0.7 (p < 0.05). The intensities, frequencies, and durations of HWEs in both geographical and social media space have high spatial heterogeneity. Its spatial variation can be explained by the type of climate zone and the unique geographical environment. The cities with extreme hot weather are more likely to adapt to the heatwave and less sensitivity to HWEs. The proposed framework, which integrates the real-time social media semantic analysis, statistical method, and spatial techniques, provides a new paradigm to assess the HWEs exposure and sensitivity analysis in China.
Keywords: China; Exposure; Heat wave events; Sensitivity; Weibo social media.
Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.