M. J. Longfritz
W. L. Siegmann
M. J. Jacobson
Rensselaer Polytech. Inst., Troy, NY 12180-3590
The representation of stochastic ensembles of sound-speed profiles by convenient and efficient means is examined. The procedure is based on using discrete empirical orthogonal functions (EOFs) with random coefficients. The eventual objective is to use the EOF representations in random wave propagation models, for which their efficiency is expected to reduce significantly the computational expense. To illustrate the procedure, two specific model ensembles are considered. The first consists of deep-water (Munk) sound-speed profiles, and the second has shallow-water profiles obtained from temperature profiles generated by a portion of the generalized digital environmental model (GDEM). After a statistical distribution of stochastic environmental input parameters is assumed, EOFs are calculated for ensembles of up to 10 000 profile samples. Relations between the statistics of the input parameters and the sound speed profiles that are obtained from EOF representations are investigated. In each case examined, the number of EOFs needed to account for virtually all of the sample variance is at most four. Additional cases are considered using Continental Shelf data by assuming measured profiles represent ensemble samples. [Work supported by ONR.]