A one-dimensional boundary layer model was used to study the effects of uncertain input data on 2-m temperature and 10-m wind. Based on a very large number of numerical results, it can be demonstrated, that even a small degree of ambiguity can have significant implications, especially for temperature. In 50 % of all 6,000 simulations for flat terrain and randomly chosen sets of input data within narrow limits, temperature uncertainty was more than 2 K, and in 14 % of all cases more than 4 K, with a maximum of 9 K. Effect on wind speed is much smaller and depends mostly on surface roughness length. For a forest scenario, the results for temperature of 18,000 simulations are in the same order, with 25 % of the ensemble show temperature uncertainties of more than 2 K, and 6 % of more than 4 K, while wind speed above a forest is much more affected than for the bare soil case. In addition, the contribution of uncertainties of individual input data was estimated.