Abstract
The availability of multiple satellite missions with wind measuring capacity has made it more desirable than ever before to integrate wind data from various sources in order to achieve an improved accuracy, resolution, and duration. A clear understanding of the error characteristics 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—are expected to evolve differently with increasing volume of available data. In this study, a collocated ocean Topography Experiment (TOPEX)–NASA Scatterometer (NSCAT)–ECMWF dataset, which covers 66°S–66°N 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 overall root-mean-square (rms) error compared to ECMWF winds, implying that they are highly converging but are systematically biased. Second, the TOPEX and NSCAT wind speed biases are characterized by a significant “phase opposition” with latitude, season, 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 point at 14.2 m s−1 coincides well with the transitional wind speed from swell dominance to wind sea dominance in wave condition, suggesting that the degree of wave development plays a key role in shaping wind speed bias.
Corresponding author address: Dr. Ge Chen, Ocean Remote Sensing Institute, Ocean University of China, 5 Yushan Road, Qingdao 266003, China. Email: gechen@public.qd.sd.cn
