Spatiotemporal dynamics of tourism climate comfort and its implications for tourism development in the Yangtze River Delta

• Assessed tourism climate comfort in the Yangtze River Delta using multi-index integration. • Identified a clear spatial gradient in TCI, with higher values in southeastern coastal cities and lower inland. • Detected a bimodal seasonal comfort pattern with lengthening autumn tourism comfort periods (+0.25 days/year). • Revealed increasing coupling coordination between climate comfort and tourism economy. Amid global climate change and rapid tourism development, tourism climate comfort has emerged as a critical metric for assessing destination attractiveness and sustainability. This study investigates the spatiotemporal evolution of tourism climate comfort in the Yangtze River Delta (YRD) from 2000 to 2020 using the Tourism Climate Index (TCI), which integrates multiple indices, including the Temperature–Humidity Index (THI), Wind Chill Index (WCI), and Clothing Index (ICL). Results indicate that TCI values were higher in southeastern coastal cities and lower in northern and inland regions, forming a clear east–west gradient. Although the regional mean TCI exhibited a slight upward trend (+0.01/year), the increase was not statistically significant (p > 0.05). We also found a distinct bimodal seasonal pattern, with spring and autumn being the most climatically suitable periods for tourism. The spring comfort period averaged 98 days (Day 63–162) and showed no significant temporal change. In contrast, the autumn comfort period lasted an average of 93 days (Day 254–347), with a marginally significant delay in the end date (+0.25 days/year, p = 0.067), suggesting a gradual extension of the season. Pearson correlation analysis showed generally positive but mostly insignificant relationships between TCI and tourism indicators, suggesting limited annual-scale influence of climate comfort compared to other socioeconomic factors. However, the increasing coupling coordination degree (CCD)—from “Uncoordinated” (mean CCD = 0.38) in 2005 to “Coordinated” (mean CCD = 0.62) in 2019—implies that despite weak direct correlations, the integrated influence of climate comfort on tourism has grown over time, highlighting its rising importance in regional tourism development. This study adds to the growing body of knowledge on tourism climate comfort and its regional dynamics by integrating multi-index climate comfort metrics with economic coordination modeling, providing quantitative insights for climate-adaptive tourism development.