Atmospheric CO2 (ca) rise changes the physiology and possibly growth of tropical trees, but these effects are likely modified by climate. Such ca × climate interactions importantly drive CO2 fertilization effects of tropical forests predicted by global vegetation models, but have not been tested empirically. Here we use tree-ring analyses to quantify how ca rise has shifted the sensitivity of tree stem growth to annual fluctuations in rainfall and temperature. We hypothesized that ca rise reduces drought sensitivity and increases temperature sensitivity of growth, by reducing transpiration and increasing leaf temperature. These responses were expected for cooler sites. At warmer sites, ca rise may cause leaf temperatures to frequently exceed the optimum for photosynthesis, and thus induce increased drought sensitivity and stronger negative effects of temperature. We tested these hypotheses using measurements of 5,318 annual rings from 129 trees of the widely distributed (sub-)tropical tree species, Toona ciliata. We studied growth responses during 1950–2014, a period during which ca rose by 28%. Tree-ring data were obtained from two cooler (mean annual temperature: 20.5–20.7°C) and two warmer (23.5–24.8°C) sites. We tested ca × climate interactions, using mixed-effect models of ring-width measurements. Our statistical models revealed several significant and robust ca × climate interactions. At cooler sites (and seasons), ca × climate interactions showed good agreement with hypothesized growth responses of reduced drought sensitivity and increased temperature sensitivity. At warmer sites, drought sensitivity increased with increasing ca, as predicted, and hot years caused stronger growth reduction at high ca. Overall, ca rise has significantly modified sensitivity of Toona stem growth to climatic variation, but these changes depended on mean climate. Our study suggests that effects of ca rise on tropical tree growth may be more complex and less stimulatory than commonly assumed and require a better representation in global vegetation models.