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GLOBAL AND REGIONAL SURFACE WIND FIELD INFERENCES FROM SPACE-BORNE SCATTEROMETER DATA 54 14 December 2002 (i.e. the same day this talk is scheduled for delivery at NRC/CATS!). For the first time, tandem scatterometer missions will return true synoptic resolution of the global ocean surface wind field. Global and regional applications of surface wind data from scatterometer systems often require regularly gridded surface vector wind fields with physically consistent treatments for missing data (e.g. due to rain contamination and/or attenuation of the radar signals). Computer models for the simulation of the ocean general circulation have been shown to be sensitive to surface wind forcing on diurnal time scales. The implied space-time requirements do not match well with the native organization of surface vector winds from scatterometer systems occurring in swaths from westward precessing orbits. A variety of statistical models have been developed to infer global and regional surface vector wind fields from scatterometer observations, on regular grids, and at diurnal temporal resolution. Blending QSCAT and Weather-Center Analysis Winds A statistical model has been developed to blend scatterometer surface vector winds with surface wind fields from weather-center analyses to create global ocean datasets, 4-times per day, at 0.5º resolution (http://dss.ucar.edu/ ds744.4). The blending methodology is constrained by an approximate power-law relation that is observed, with regional and monthly variability, in wavenumber spectra for surface winds from scatterometer systems. The weather- center winds are used only in swath gaps and missing data regions with respect to the QSCAT orbits. They must be augmented at high wavenumbers to retain the regional and seasonal power-law relation that is observed. The augmentation is implemented in a multi-resolution wavelet procedure designed by Chin et al (1998). Figure 1 depicts three panels of the global wind stress curl field for 24 January 2000 at 1800 UTC. The wind stress curl is a scalar summary of the surface vector wind field that is useful to illustrate the blending method. The top panel shows the wind stress curl from the weather-center analyses field. Analysis fields combine the latest forecast field with relevant surface observations that accrue over the forecast interval (e.g. between initialization and verification times). In the middle panel, the wind stress curl derived in the QSCAT swaths for this time period are superposed on the analysis field. Note the higher wavenumber content in the surface wind stress curl from the satellite observations. The blending method operates to augment the higher wavenumber content of the weather-center analyses such that the
