The aim of this study was to investigate the effect of climate variables on monthly growth in diameter and height of Araucaria angustifolia (Bert.) O. Kuntze and of Pinus taeda L., over a six-year period, as well as verifing the contribution of these variables in the composition of the Chapman-Richards model. To this end, we selected 30 trees of each species and measured monthly the diameter and height, between June 2006 and August 2012. The climate variables were obtained from two SIMEPAR meteorological stations near the plantings. A correlation matrix was constructed to determine the effect of climate variables on the monthly growth. Next a principal component analysis (PCA) was conducted to determine the climate variables to be included in the fit of the Chapman-Richards model. The results indicated that the climate variables with the highest correlation (about 0.6) with monthly growth in diameter and height of the species were temperature, photoperiod and atmospheric pressure, and precipitation for some years of the study. The fitted model that included climate variables showed reduced Syx% of about 0.8% compared to the traditional biological model. However, ANOVA showed no statistical difference between the production estimates obtained by both models.