Global air-sea flux of carbon dioxide (CO2) is calculated from wind data acquired by the satellite scatterometer QuikSCAT, the passive microwave radiometer AMSR-E, and the model reanalysis ERA-40 using four of the most commonly used wind speed dependent parameterizations of gas transfer velocity. Assuming QuikSCAT as reference, the results are compared to obtain an estimate of that relative uncertainty in the flux calculations which results solely from the origin of the input wind data. We illustrate the discrepancies between these data sets and quantify the uncertainty in the computed air- sea CO2 flux that arises from data processing such as temporal and spatial averaging using AMSR-E as an example data set. The impact of temporal variability of wind speed is shown to be significantly greater than that of spatial variability. However, simple arameterizations of temporal variability are found to be sensor-specific and cannot be applied in a straightforward way to data sets with lower temporal resolutions from other sensors. We show a simple methodology to correct monthly mean data in such a way that seasonally and zonally varying parameterizations of temporal variability derived from QuikSCAT data can be applied to data from AMSR-E and ERA-40. This allows us to produce a global 44-year time series of gas transfer velocity and to present a more coherent estimate of air- sea transfer of carbon dioxide from the three most commonly available types of wind data.