Research on the urban public perception of different rainfall types in China

Given global climate change and rapid urbanization, China is having diverse types of rainfall and frequent extreme rainfall events. Utilizing semantic information from geotagged social media dataset, to study the rainfall perception patterns under different rainfall types and identify the rainfall types that cause public disaster perceptions is of great significance for urban management and disaster response. In this study, we extracted over 780,000 rainfall related microblogs from 210 million microblogs and studied urban public perception of various rainfall types in China, rather than focusing on a single event or city. The contributions of this study are: (1) Identify the spatial and thematic patterns perceived by the public in 213 cities (for example, ML, MH and HH are the most sensitive rainfall types on microblogging), and comprehensively understand how rainfall characteristics (duration and intensity) affect public attention. (2) Reveal the types of rainfall causing disaster perception (such as HH and MH) and their specific contents, which are different from the officially defined rainstorm events. 33.2 % of cities also perceive disaster under non rainstorm events. (3) Determine the rainfall types that lead to disasters and disaster impacts through public perception, provide feasible insights for urban management, and enhance the decision-making of disaster risk reduction and infrastructure planning.