National and regional climate-sensitive biomass equations were developed for poplar plantations in China, with mean annual temperature and precipitation significantly affecting predicted biomass. In the context of global climate change, information on forest biomass becomes more and more important, and the impact of climate change on biomass estimation is also receiving increasing attention. Using the dummy variable modeling approach and the error-in-variable simultaneous equations approach, national and regional one- and two-variable individual tree biomass models were developed for poplar plantations in China. The models were based on above- and below-ground biomass data of 450 and 147 destructive sample trees, respectively, collected from poplar plantations in 15 provinces of three regions in China. In addition, combined with climate data of mean annual temperature (T) and mean annual precipitation (P), climate-sensitive individual tree biomass models were established, and the impact of climatic factors on biomass estimation was analyzed. The coefficients of determination of national above- and below-ground biomass models developed in this study were more than 0.90 and 0.82, whereas the mean prediction errors were less than 5% and 10%, respectively. For climate-sensitive biomass models, aboveground biomass was only impacted by T, while belowground biomass was affected by both T and P, and impact of the latter was greater than that of the former. Considering the comprehensive effect of climatic factors to above- and belowground estimation, the total biomass estimates of poplar trees with the same size would reach the maximum in the regions for T = 17 °C and P = 1200 mm, which might provide reference for the scientific management of poplar plantations in China.