The synthetic experiments are implemented to investigate the impact of different environmental conditions on the uncertainty of thermal diffusivity estimates. We generate synthetic temperature fields that represent various types of temperature gradients and fluctuations. This is achieved through forward modeling (i.e., heat-conduction process in a heterogeneous medium using an explicit finite difference method) with initial, top, and bottom boundary conditions set equal to the temperature time series observed at a monitoring site in Alaska during summer (synthetic_data_summer.csv ) and autumn (synthetic_data_autumn.csv ), and by assuming a soil column composed of three layers (i.e., top layer at 0.05–0.1 m, middle layer at 0.1–0.42 m, and bottom layer at 0.42–1.05 m). The thermal diffusivity in the three layers is assumed to be constant over time and equal to 0.16, 0.27 and 0.43 mm2s−1 for the case of summer temperatures and 0.25, 0.75 and 0.6 mm2s−1 for autumn. Each .csv file has 14 columns: first column containes information on the date and time on which temperature was recorded, the remaining 13 columns are soil temperature at 0.05, 0.10, 0.15, 0.20 0.25, 0.35, 0.45, 0.55, 0.65, 0.75, 0.85, 0.95 and 1.05 m below the ground surface. Impact of soil temperature trend and fluctuations on thermal diffusivity estimates is evaluated for various synthetic temperature fields including (a) summer trend and fluctuations (synthetic_data_summer.csv ), (b) detrended fluctuations (synthetic_data_summer_detrended.csv ), (c) smoothed out daily and smaller fluctuations (synthetic_data_summer_noDiurnalFluct.csv), and (d) without fluctuations (synthetic_data_summer_noFluct.csv ).