Application of similarity theory to forecasting the mixed-layer depth of the ocean.

Abstract

The thermal structure of the ocean, especially the uppermost mixed layer, greatly affects sonar ranges. In this paper, similarity theory is applied to the problem of forecasting the depth of the mixed layer during the warm season, assuming the controlling processes are secular, non-advective , and non-divergent. The resulting forecast method consists mainly of two equations. Parameters used are wind, coriolis effect, the coefficient of thermal expansion and a measure of the excess heat within the mixed layer. The constants in the equations were determined using data from OWS Papa (50N, 145W). The forecast method treats both seasonal and transitional thermoc lines . The method was tested with data from OWS Papa and OWS November (30N, 140W). The tests apparently indicate wide applicability of this forecast method and thus tend to corroborate the proposal by Kitaigorodsky that the mixed- layer depth is a function of a universal coefficient.