Innocent Souopgui (University of New Orleans, USA); Clark Rowley (Naval Research Laboratory, USA); Scott Smith (Naval Research Laboratory, USA); Gregg Jacobs (Naval Research Laboratory, USA); Robert Helber (Naval Research Laboratory, USA); Max Yaremchuk (Naval Research Laboratory, USA)

We demonstrate the successful assimilation of simulated Surface Water Ocean Topography (SWOT) observations into a high-resolution forecast model using a multi-step 3DVAR analysis procedure. The first analysis step seeks to correct the large-scale, while the second step seeks to correct for the smaller-scale features present in the SWOT observations. An Observing System Simulation Experiment (OSSE) is used to explicitly calculate errors produced by competing single- and multi-scale analysis procedures. The first analysis step is the standard exploitation of observations with a 5-day data analysis period, horizontal correlation scales, vertical structure, and background errors consistent with mesoscale corrections. Experimentation with the observation window length of the second analysis step shows that a shorter time window produces lower analysis errors. This is consistent with the larger mesoscale structures having a longer time period and submesoscale structures having short Eulerian times being advected by the mesoscale. Therefore, a 24-hour observation window with a first guess at appropriate time (FGAT) for the second step was selected and sequential analysis/forecast cycles were performed for an entire year. The multi-scale analysis produces less overall error than the single-scale analysis when analyzing both area-averaged errors and wavenumber spectral analysis. Therefore, the multi-scale assimilation is essential for most effectively utilizing the forthcoming SWOT observations, which resolve features across a much wider spectrum of horizontal scales than are observed by the current nadir altimeters.