Accurate climate data is fundamental for ecological modeling and forest management to adapt to climate change. Gridded climate datasets often fail to capture local variability, especially in regions with complex terrain. In this study, we compare two open data sources: WorldClim, a widely used gridded dataset, and ClimateAP, a scale-free dataset that generates point-specific climate information for the first time. We evaluated their performance by comparing outputs against observations from 2,340 weather stations (1961 to 1990) across Mainland China. Our analysis showed that ClimateAP yielded higher adjusted R² values (>0.90), lower mean absolute error, and higher regression coefficient across temperature and precipitation variables. These improvements were most pronounced in complex terrain and during summer months, where ClimateAP’s predictions showed up to 15% higher accuracy than WorldClim. We also applied ClimateAP data to develop climate niche models for Cunninghamia lanceolata and Pinus massoniana using a Random Forest algorithm. Models based on ClimateAP data show better performance, with lower out of bag error rates (17.70 percent versus 19.23 percent for Cunninghamia lanceolata and 15.67 percent versus 17.89 percent for Pinus massoniana). Our study provides quantitative evidence to guide the selection of open climate data sources for ecological analyses.