A technique for objective analysis and design of oceanographic experiments applied to MODE-73

Abstract

A technique for the objective analysis of oceanic data has been developed and used on simulated data. The technique is based on a standard statistical result—the Gauss-Markov Theorem-which gives an expression for the least square error linear estimate of some physical variable (velocity, stream function, temperature, etc.) given measurements at a limited number of data points, the statistics of the field being estimated in the form of space-time spectra, and the measurement errors. An expression for the r.m.s. error expected in this estimate is also derived and illustrated in the form of ‘error maps’.

Efficient sampling arrays can be designed through trial-and-error adjustment of array configurations until a suitable balance of mapping coverage and accuracy, as measured by the error maps, is achieved. Examples of the mapping ability of some simple arrays are given.

Using statistics inferred from the preliminary Mid Ocean Dynamics Experiments various realizations of likely flow fields were simulated. The 16 element MODE-I array was tested by comparison of the simulated fields and the objective maps based on inferred ‘measurements’ at the array points. The reliability of statistics inferred from observations was estimated by comparing correlations derived from limited observations of the simulated fields with the known statistics. Correlations derived from two realizations differed significantly but most calculations reproduced the known statistics moderately well.

An intercomparison of Eulerian measurements (current meters) and Lagrangian measurements (neutrally buoyant drifters) was also carried out using the objective interpolation method.