Net primary productivity (NPP) is an important index to evaluate the carbon budget of forest ecosystems. It is of great significance to accurately assess the changes of forest NPP to cope with climate change. Based on the Biome-BGC model with localized parameters, we simulated the dynamics of NPP in six typical subtropical forests in Xiuhe River Basin of Jiangxi Province during 1960-2021, and analyzed the responses of forest NPP to temperature and precipitation under different climate scenarios. The results showed that: (1) From 1960 to 2021, the NPP of different forest types was in order of bamboo forest (655.20 g C·m^-2·a^-1) > evergreen coniferous forest (629.42 g C·m^-2·a^-1) > evergreen broad-leaved forest (600.01 g C·m^-2·a^-1) > evergreen coniferous and broad-leaved mixed forest (596.98 g C·m^-2·a^-1) > deciduous broad-leaved forest (325.20 g C·m^-2·a^-1) > shrub (266.43 g C·m^-2·a^-1). (2) As for the inter-monthly variation of NPP, deciduous broad-leaved forest showed a unimodal trend and reached the highest value in August, while other forests decreased to a bimodal trend in August. Except for deciduous broad-leaved forest and shrub forest, the NPP of forests showed a significant negative correlation with temperature from July to September, but a positive correlation with precipitation, indicating that increased temperature and decreased precipitation in summer greatly affected vegetation growth. (3) According to the fitting strength of meteorological factors, the response strength of NPP to temperature was greater than that of precipitation, and the fitting strength of temperature to NPP of bamboo forest and deciduous broad-leaved forest was stronger (R²>0.46; P<0.01). The correlation between precipitation and NPP in evergreen coniferous forest, bamboo forest, shrub forest and broad-leaved deciduous forest was relatively weak (R²<0.21; P<0.01). (4) In the future climate scenario, appropriate temperature increase is helpful to promote vegetation growth, but NPP will be inhibited when temperature increase exceeds the threshold. In the precipitation scenario, NPP is positively correlated with precipitation. The response range of NPP to temperature is much greater than that of precipitation, and the effect of the combination of temperature and precipitation is stronger than that of the single change scenario.