Sensitivity analysis is crucial for identifying key crop model parameters to improve parameterization efficiency, but climate conditions can affect sensitivity, leading to inaccurate calibration if different climate conditions are not considered. This study uses the extended Fourier amplitude sensitivity test to identify sensitive cultivar parameters in the Agricultural Production System Simulator (APSIM-Maize), focusing on maize yield in a semiarid region. Regression analysis shows that rainfall and maximum temperature significantly impact the sensitivity of maize yield to the transpiration efficiency coefficient ( transp_eff_cf ) (r =-0.66 and 0.63, p = 0.001 and 0.003, respectively) and grain growth rate ( grin_gth_rate ) (r = 0.74 and-0.70, p = 0.0002 and 0.0005, respectively). The sensitivity of maize yield to the thermal time from emergency to the end of juvenile ( tt_e- merg_to_endjuv) shows varying sensitivity across years ( ST i = 0.03-0.26), influenced by maximum temperature. Our results demonstrated that transp_eff_cf and grain_gth_rate should be adjusted cautiously, especially in drier or warmer conditions. The implications of our study extend to providing valuable support for the calibration of APSIM-Maize cultivar parameters in response to climate variability.