The availability of muhiple sateilite missions with wind measuring capacity has made it more desirable than ever before to integrule wind data from various sources in order to achieve an improved accuracy, resolution. and duration. A clear understanding of the error charaeterlsties associated with each type of data is needed for a meaningful merging or combination. The two kinds of errors-namely, random error and systematic error-ate expected to evolve differently with increasing volume of available data In this study, a collocated ocean Topography Experiment (TOPEX)-NASA Seatterometer (NSCAT)-ECMWF dataset, which covers 66S-66N and spans the entire 10-month lifetime of NSCAT. is compiled to investigate the systematic discrepancies among the three kinds of wind estimates, yielding a number of interesting results, First, the satellite derived wind speeds are found to have a larger overall bias but a much smaller ovemli foot-mean-square (rms) error compared to ECMWF winds, implying thai they are highly converging but are systemalically biased. Second. the TOPEX and NSCAT wind speed biases are characterized by a significant "'phase opposition" with latitude, seasnn, and wind intensity, respectively. Third. the TOPEX (NSCAT) bias exhibits a low-high-low <high-low-high) pattern as a function of wind speed, whose turning poim at 14.2ms-1 coincides well with the transitional wind speed flora swell dominance to wind sea dominance in wave condition, suggesting that the degreee of wave development plays a key role in shaping wind speed bias.