Using routine hydrographic sections for estimating the parameters needed for Optimal Statistical Interpolation. Application to the northern Alboran Sea

Abstract

Optimal Statistical Interpolation is widely applied in the analysis of oceanographic data. This technique requires knowing some statistics of the analysed fields such as the covariance function and the noise to signal ratio. The different parameters needed should be obtained from historical data sets, but, in contrast with the case of meteorology, these data sets are not frequently available for oceanographic purposes. Here we show that using routine hydrographic samplings can provide a good estimate of the statistics needed to perform an Optimal Statistical Interpolation. These data sets allow the covariance function to be estimated between two points with different horizontal and vertical coordinates taking into account the possible lack of homogeneity and isotropy which is rarely considered. This also allows us to accomplish a three-dimensional analysis of hydrographic data, which yields smaller analysis errors than a traditional two-dimensional analysis would.