Time and space scales for sea surface salinity in the tropical oceans

Seasonal cycles of surface layer salinity in the Pacific Ocean

“…Delcroix et al, 1996;Delcroix and Henin, 1991, henceforth DH91;Delcroix et al, 2005). DH91 looked at seasonal variability averaged from bucket data along a series of volunteer observing ship tracks in the tropical Pacific.…”

Data assimilation of simulated SSS SMOS products in an ocean forecasting system

“…41 Another interesting method could be based on recent studies that used turbulent exchange coefficients estimates from sequential data assimilation to improve bulk formulae 42 in oceanic models with a free-surface formulation. Finally, the extension of SSS assimilation in a global model (medium and/or high resolution) in order to apprehend important physical processes in Pacific and Tropical regions 8,43 is also essential.…”

“…5,6 In the tropical Pacific Ocean, El Niño-Southern Oscillation (ENSO) related SSS changes are strongly related to ENSOrelated precipitation changes, and a study 7 shows that having a continuous remotely sensed SSS data might add considerably to ENSO predictions at longer lead times as a result of improved knowledge of SSS-induced changes in the subsurface density field. Moreover, Delcroix et al 8 shows that the SSS timescale is found to be generally less than three months in regions that have strong seasonal cycles, whereas timescales range between 4-8 months where the variability is mostly controlled by ENSO.…”

Decorrelation scales for Arctic Ocean Hydrography. Part I: Amerasian Basin

“…The functional form of the autocorrelation depends on the physical properties, the considered scales (e.g., synoptic versus mesoscale) and the area. Many studies have estimated autocorrelation functions through analysis of in-situ ocean measurements [e.g., Meyers et al, 1991;Chu et al, 2002;Delcroix et al, 2005] and satellite observations [e.g., Kuragano and Kamachi, 2000;Hosoda and Kawamura, 2004;Tzorti et al, 2016]. Generally the estimated autocorrelation functions have exponential or Gaussian form [Molinari and Festa, 2000].…”

“…In optimal interpolation and objective mapping, the decorrelation scale gives a measure of influential radius of a point measurement; the autocorrelation function, together with the associated decorrelation scale, provides the weight of a point measurement on mean field estimates Chu et al, 1997;Davis, 1998;Wong et al, 2003;Böhme and Send, 2005]. For observation network design, decorrelation scales are one guide to estimate optimal sampling intervals in space and time [S printall and Meyers, 1991;White, 1995;Delcroix et al, 2005].…”