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Abstract. The effect of diurnal variations in sea surface temperature (SST) on the air-sea flux of CO 2 over the central is evaluated for [2005][2006]. We use high spatial resolution hourly satellite ocean skin temperature data to determine the diurnal warming ( SST). The CO 2 flux is then computed using three different temperature fields -a foundation temperature (T f , measured at a depth where there is no diurnal variation), T f plus the hourly SST and T f plus the monthly average of the SSTs. This is done in conjunction with a physically-based parameterisation for the gas transfer velocity (NOAA-COARE). The differences between the fluxes evaluated for these three different temperature fields quantify the effects of both diurnal warming and diurnal covariations. We find that including diurnal warming increases the CO 2 flux out of this region of the Atlantic for 2005-2006 from 9.6 Tg C a −1 to 30.4 Tg C a −1 (hourly SST) and 31.2 Tg C a −1 (monthly average of SST measurements). Diurnal warming in this region, therefore, has a large impact on the annual net CO 2 flux but diurnal covariations are negligible. However, in this region of the Atlantic the uptake and outgassing of CO 2 is approximately balanced over the annual cycle, so although we find diurnal warming has a very large effect here, the Atlantic as a whole is a very strong carbon sink (e.g. −920 Tg C a −1 Takahashi et al., 2002) making this is a small contribution to the Atlantic carbon budget.

[1] Global air-sea flux of carbon dioxide (CO 2 ) 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 CO 2 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 parameterizations 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.

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