Optimizing and applying a tourism climate comfort model in humid-rainy regions: The case of Guilin, China.

In the context of global climate change, accurate assessment of tourism climate comfort is of great significance for sustainable tourism development. However, when existing general models are applied to humid and rainy climate regions, they exhibit notable deficiencies in evaluating the combined impacts of persistent high humidity and heavy precipitation. To address this issue, this study takes Guilin, China as a case study. Based on the Holiday Climate Index (HCI), dynamic correction factors for humidity and precipitation are introduced to develop an optimized model, MHCI2, suitable for humid monsoon climate regions. The regional applicability of the model is comprehensively evaluated by combining long-term meteorological data with tourist perception questionnaires. The results show that: (1) MHCI2 more reasonably characterizes the spatiotemporal variation of tourism climate comfort in Guilin, and its outputs show directional monthly-scale consistency with the monthly trends in tourist acceptance rates. When MHCI2 > 63, the tourist acceptance rate typically exceeded 80%, indicating that this value can serve as an indicative empirical reference benchmark for tourism climate suitability in the Guilin region.(2) Guilin's tourism climate exhibits a "double-valley comfort" pattern: spring high humidity and summer heavy precipitation each cause declines in comfort, while autumn (September to November) is the most suitable tourism period of the year. (3) Compared with traditional models, MHCI2 more effectively identifies the inhibitory effects of high humidity and precipitation on comfort, avoiding the overestimation of summer comfort. This study provides a methodological reference for tourism climate adaptability assessment in humid and rainy regions, and offers empirical support for destination seasonal management, optimization of tourist services, and climate risk management.