Extremely high temperatures have become a major hurdle to tourists' experiences in various destinations. In this study, we present the first nationwide estimation of the temperature-tourism response function using a fine-grained panel dataset constructed by matching tourism data and daily meteorological datasets for 280 cities from 2005 to 2019 in China. Results show a non-linear relationship between temperature and tourism employing the temperature bins method, which is not sensitive to response equations. In addition, we conduct a rich heterogeneity analysis in the article to further analyse the effects of other external conditions on the temperature-tourism relationship, including the destination's level of tourism economic development, population, infrastructure development, and tourism resource endowment. We also observed that increasing summer temperatures result in decreased tourism arrivals and revenue, while rising autumn temperatures lead to increased tourism arrivals and revenue. This research contributes to a deeper understanding of the complex relationship between temperature dynamics and tourism patterns, offering insights into destination management and adaptation strategies.