As China undergoes a rapid transition into an aging society, the mobility challenges faced by the older adults in high-density mountainous cities are exacerbated by complex topographical conditions. Existing studies often overlook the nonlinear relationships and the distinct planning requirements of mountainous versus flat urban areas when evaluating the age-friendliness of community parks. This study aims to identify the critical elements of age-friendly planning in mountainous community parks, validate the applicability of nonlinear models, and quantify the dynamic effects of various factors on older adults’ satisfaction, thereby establishing a foundation for targeted optimization strategies. Utilizing principal component analysis (PCA) on 358 valid questionnaires collected from three representative mountainous community parks in Chongqing, six key planning factors were extracted. An ordered logit model was employed for regression and marginal effect analyses. The findings reveal that (1) the ordered logit model outperforms alternative models in terms of goodness-of-fit and computational efficiency, making it particularly suitable for capturing the nonlinear characteristics of satisfaction; (2) accessibility facilities, spatial and social connectivity, and landscape environment emerge as the primary determinants of older adults’ satisfaction, with improvements in accessibility facilities exerting the most significant impact; and (3) the provision of multifunctional activity spaces and increased social opportunities effectively addresses the psychological and physiological needs of the older adults. This study contributes to the optimization of age-friendly design strategies for community parks in high-density mountainous cities, offering valuable insights for promoting healthy aging and fostering inclusive urban environments.

Vegetation physiological processes are critical regulators of terrestrial carbon–water cycles and local microclimate dynamics, with photosynthetically active radiation (PAR, 400–700 nm) serving as a primary driving force. However, most vegetation–climate process models simplify the fraction of PAR in global solar radiation as a constant 50%, potentially introducing diurnal simulation biases that propagate into cumulative annual errors in vegetation carbon–water coupling estimates. To address this limitation, we first evaluated the performance of three empirical models for simulating the dynamic PAR fraction and integrated the most accurate model into the Vegetation Microclimate Process (VMcP) model, and further used typical meteorological year (TMY) data of Beijing, Shanghai and Shenzhen as input to compare the differences in vegetation carbon–water processes before and after the improvement. The results show that the diurnal variation range of PAR fraction in global solar radiation is between 39% and 58%. The existing models that neglect the dynamic changes in PAR may overestimate vegetation transpiration cooling and photosynthetic carbon sequestration by 2.3% and 3.5%, respectively. Meanwhile, Shenzhen (64.3 W/m²; 1.59 g/m²·d), characterized by favorable light and thermal conditions, is more prone to large errors compared with Shanghai (47.6 W/m²; 1.21 g/m²·d) and Beijing (39.5 W/m²; 0.93 g/m²·d). This study provides a novel tool for the accurate assessment of vegetation-mediated microclimate improvement, and offers a new perspective for nature-based climate solutions.