Reconstructing Synthetic Profiles from Surface Data

Abstract

A method for the extrapolation of vertical profiles of temperature (and/or steric heights) from measurements of sea surface elevation and sea surface temperature has been developed and is described here. The technique, called coupled pattern reconstruction (CPR), is based on a multivariate analysis of the coupled variability of vertical profiles from historical hydrographic data and on the hypothesis that only few modes are needed to explain most of the covariance of the fields. Through a linear regression between the amplitudes of the coupled modes it is possible to reconstruct the first two modes by solving a simple linear system written for the surface values, which are supposed to be known. The CPR method has been applied and tested on 9 yr of conductivity? temperature?depth (CTD) measurements collected in the northern Mediterranean Sea during the Dynamiques des Flux de Matière en Mediterranée (DYFAMED) program (1994?2002). The first 6 yr were used as a training dataset, while the last 3 were set aside as independent test measurements. Results have demonstrated a substantial improvement in terms of absolute error with respect to an ad hoc climatology, and slightly worse performances compared to the most advanced technique found in literature, which consists of the single empirical orthogonal function reconstruction (sEOF-R) through a multivariate regression of the amplitudes, except for the very first meters. However, CPR is demonstrated to be much more robust and better performing with respect to sEOF-R when considering the errors associated with real measurements of sea surface elevation.