A Regression Method for Estimating Salinity in the Ocean

K. A. Korotenko

Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia
e-mail: lkorotenko@mail.ru

Received March 20, 2006; in final form, June 7, 2006

Abstract—Specification of salinity is an important problem in initialization of the global ocean circulation
models. Unlike the temperature, the salinity data in the World Ocean are irregular and nonuniform; thus, meth-
ods for estimating the salinity using pleutiful temperature data are urgently needed. A new regression method
for estimating the salinity in the ocean is suggested in this paper. Unlike similar currently known approaches,
the method suggested applies a set of polynomials and their powers invariant for the entire ocean, while the
latter is divided into a number of study subregions for the estimates. The best-fit regression curves and the min-
imal errors of the salinity estimates are found for each of the regions. The method uses the World Oceano-
graphic Database (WOD-2001 NODC NOAA) to determine the regression coefficients and the confidence
intervals (RCCI). A special RCCI database was organized on the basis of these data. The RCCI database makes
possible determination of the salinity at any point in the ocean if the temperature data are provided (measure-
ments, XBT profiles, etc.). A realization of the method suggested is demonstrated by the example of the Atlantic
Ocean.

DOI: 10.1134/S0001437007040030

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