A Regression Model for Estimating Salinity in the South Eastern Mediterranean Sea

Maged Mohamed Abdel Moneim Hussein

doi:10.11648/j.ijema.20160402.13

Maged Mohamed Abdel Moneim Hussein

Open Access

https://doi.org/10.11648/j.ijema.20160402.13

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Abstract

This paper attends the problem of estimating salinity for a southeastern Mediterranean Sea. The main objective of the present study is the estimation of salinity profiles in the upper 500m from measurements of temperature profiles and surface salinity. 465 Temperature and salinity profiles were selected for this study, taken from expeditions carried out by research vessels Yakov Gakkov and Vladimir Parshin, of former Soviet Union during the period 1987-1990. The empirical relationship between salinity and temperature in southeastern Mediterranean Sea is quantified with the help of local regression. Differences in salinity's co-variability with temperature and with longitude, latitude and day of year from eastern to western part of the study area suggested that the region may be achieving more accurate salinity estimates. Eight methods were used for estimating salinity profiles in the present study. The results obtained from method 5 (Surface salinity added to fourth degree polynomial of temperature) were better than other methods for the upper 130m, while method 8 (longitude, latitude and day of year added to third degree polynomial of temperature) were better for the rest depths.

Highlights

Seawater temperature (T) measurements are much cheaper and easier to do than the measurements of salinity (S) ; the temperature values dataset is much bigger than the salinity values dataset
The present paper aims to carry out suitable regression methods to estimate salinity profiles in the upper 500m from temperature profiles measurements, sea surface salinity and other correlates of salinity in the southeastern Mediterranean Sea
465 temperature and salinity profiles were selected for this study, has been taken from research vessels Yakov Gakkov and Vladimir Parshin, of former Soviet Union during spring months of the period 1987-1990

Summary

Introduction

Seawater temperature (T) measurements are much cheaper and easier to do than the measurements of salinity (S) ; the temperature values dataset is much bigger than the salinity values dataset. The implementation of multi-parametric data assimilation schemes in ocean forecasting models presuppose the use of factual salinity values estimated from temperature profiles. The logical way is based some physical assumptions and climatology datasets [1]. There is no dynamical relationship between temperature and salinity, but temperature and salinity can present strong empirical relationships within the different water masses. There is a global need to estimate the salinity. The relationship between Salinity and temperature and other observables varies spatially and depend on the region. The mission of developing capability for salinity estimation must be approached spatially region by region [2]

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