Use of an optimum interpolation method to construct a high-resolution global ocean surface vector wind dataset from active scatterometers and passive radiometers

ABSTRACT

This study presents a new 0.25° gridded 6-hourly global ocean surface wind vector dataset from 2000 to 2015 produced by blending satellite wind retrievals from five active scatterometers (QuikSCAT, ASCAT-A, ASCAT-B, OSCAT, and HY-2A), nine passive radiometers (four SSM/I sensors, two SSMIS sensors, TMI, AMSR-E, and AMSR2) and one polarimetric radiometer (WindSat) with reanalysis from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) employing an optimum interpolation method (OIM). The accuracy of this wind product is determined through various comparisons with buoy measurements, NCEP/NCAR reanalysis and the cross-calibrated multi-platform (CCMP) winds. The comparisons indicate that OIM winds agree well with buoys, showing a root-mean-squared difference of 1.32 m s⁻¹ for wind speed and 24.73° for wind direction over 0–30 m s⁻¹ wind speed range. And the quality of OIM winds is improved significantly relative to NCEP/NCAR reanalysis and can be comparable with CCMP winds. Furthermore, OIM winds can reveal abundant small-scale features that are not visible in reanalysis data. In addition, the wind speed and direction retrievals of most satellites are proved to play an important role in generating the high-quality product, but the procedure for including HY-2A winds and WindSat wind directions should be further explored.

Acknowledgements

The datasets of SSMI, SSMIS, TMI, AMSRE, AMSR2, WindSat, and CCMP were downloaded from Remote Sensing Systems. QuikSCAT and ASCAT datasets were downloaded from NASA JPL PO.DAAC, and HY-2A data was obtained from NSOAS. The original ASCAT dataset is hosted by KNMI. The buoy winds were downloaded from NOAA. The NCEP/NCAR reanalysis winds were downloaded from NOAA Earth System Research Laboratory. The authors thank these scientific research groups very much for providing these datasets.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study is supported by the National Key Research and Development Programme of China [contract number 2016YFA0600102]; the National High Technology Research and Development Programme (863 Programme) of China [contract number SS2013AA091206].