The air temperature (T-air), total precipitation (TP) and potential evapotranspiration (PET) are standard input data for soil carbon dynamic models, i.e., for calculating temperature and moisture effects on soil biological activity. The resolution needed depends on objectives, the complexity of models and inbuilt pedotransfer functions. The Introductory Carbon Balance Model (ICBM) soil climate front end model calculates a multiplicative soil-temperature (r(e_temp)) and -moisture (r(e_wat)) factor with a daily time-step to estimate soil biological activity, i.e., r(e_crop) = r(e_temp) x r(e_wat). Our objective was to determine how much re_temp. r(e_wat) and r(e_crop) are affected by low-pass filtering of the climatic input data for a cool, humid temperate region. To achieve this we conducted spectral analysis on T-air, TP, PET and r(e_crop) in the frequency domain. Thereafter we applied Fourier low-pass filters of 5, 15, 30, 60 and 180 days on T-air, TP, PET and tracked their effects through the soil climate model's state variables and outputs. This was done using a sandy and a heavy clay soil and an 89-year daily time-series from a meteorological station in Quebec (Canada). The Fourier spectra showed that the variance for T-air, PET and r(e_temp) was dominated by an annual cycle, as could be expected. There was no yearly cycle for TP. The variation in r(e_temp) explained most of the variance in r(e_crop). The soil climate module outputs were not sensitive to low-pass filtering of PET. A daily time-step was needed to avoid overestimating r(e_crop) for the sandy soil. Using a weekly time-step for TP and T-air allowed us to explain about 80% of the variance in r(e_crop) for the heavy clay soil. This study also indicates that the standard leaf (and green) area index functions for calculating transpiration should receive more attention, since they have significant effects on the state and output variables. (C) 2011 Elsevier B.V. All rights reserved.