Extending the dataset set up with ERS-1, ERS-2 and NSCAT series, CERSAT provides the scientific community with easy-to-use synoptic gridded fields of wind-related parameters (speed and stress vectors), estimated from observations by NASA scatterometer SeaWinds onboard QuikSCAT. They are provided with three time resolutions - daily, weekly and monthly averages - on a global 0.5°x0.5° resolution grid, since July 1999. The data are available in netCDF format and quicklook pictures are also provided.
The QuikSCAT mean wind fields (refered as QuikSCAT/MWF product) consist of global winds over the ocean. They are the latest of several surface products containing scatterometer derived winds over the oceans produced by CERSAT/IFREMER. A geostatistical method, known as kriging method, was used to estimate these new surface wind analyses between 80S and 80N latitude from QuikScat wind observations (JPL/PO.DAAC L2B product).
They are distributed as global half-degree resolution geographical grids. Main parameters included are wind vector (wind speed, components and divergence) and wind stress (magnitude, components and curl). The standard errors of the parameters estimated by this objective analysis are also included as complementary fields. The fields are estimated over three different time resolutions : daily, weekly and monthly.
The product quality was assessed through comparisons against buoys and ECMWF analysis (these validation results are featured within the user manual). The QuikSCAT/MWF product is currently being used in model forcing experiments and already appears as a valuable alternative to model results. It is also part of upcoming WOCE DVD to be released in November 2002.
Data (supplied as netCDF files), manual and quicklooks can be obtained from CERSAT ftp server and web site. Information, comments or requests can be addressed to Abderrahim Bentamy ( Abderrahim.Bentamy@ifremer.fr) or Jean-Francois Piolle ( Jean.Francois.Piolle@ifremer.fr).
Check the related section (Data > Catalog > Gridded products > MWF-QuikSCAT) for more details.