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

Maged Mohamed Abdel Moneim Hussein

doi:doi:10.11648/j.ijema.20160402.13

| Peer-Reviewed

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

Maged Mohamed Abdel Moneim Hussein

Published in International Journal of Environmental Monitoring and Analysis (Volume 4, Issue 2)

Received: 15 March 2016 Accepted: 24 March 2016 Published: 5 April 2016

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

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.

Published in	International Journal of Environmental Monitoring and Analysis (Volume 4, Issue 2)
DOI	10.11648/j.ijema.20160402.13
Page(s)	56-64
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Mediterranean Sea, Salinity, Temperature Profile, Regression

References

[1]	F. Reseghetti, "Empirical reconstruction of salinity from temperature profiles with phenomenological constrains". Ocean Science Discussion, (2007), (4), 1-39.
[2]	W. C Thacker, "Estimating salinity to complement observed temperature: 1. Gulf of Mexico". Journal of Marine Systems, (2007), (65), 224-248.
[3]	H. Stommel, "Note on the use of the T–S correlation for dynamic height anomaly calculations". Journal of Marine Research, (1947), (6), 85–92.
[4]	W. C Thacker, "Estimating Salinity between 25° and 45° in the Atlantic Ocean using Local Regression". Journal of Atmospheric and Oceanic Technology, (2008), (25), 114-130.
[5]	G. R. Flierl, "Correcting expendable bathythermograph (XBT) data for salinity effects to compute dynamic heights in Gulf Stream rings". Deep-Sea Research, (1978), (25), 129–134.
[6]	J. R. Donguy, G. Eldin, and K. Wyrtki, "Sea level and dynamic topography in the western Pacific during 1982–1983 El Nino". Tropical Ocean-Atmosphere Newsletter, (1986), (36), 1–3.
[7]	W. S. Kessler, and B. A. Taft, "Dynamic heights and zonal geostrophic transports in the central tropical Pacific during 1979 –1984". Journal of Physical Oceanography, (1987), (17), 97–122.
[8]	A. Troccoli, and K. Haines, "Use of the temperature – salinity relation in a data assimilation context". Journal of Atmospheric and Oceanic Technology, (1999), (16), 2011–2025.
[9]	F. C. Vossepoel, R. W. Reynolds, and L. Miller, "Use of sea level observations to estimate salinity variability in the tropical Pacific". Journal of Atmospheric and Oceanic Technology, (1999), (16), 1401–1415.
[10]	D. V. Hansen, and W. C. Thacker, "Estimation of salinity profiles in the upper ocean". Journal of Geophysical Research, (1999), (104), 7921–7933.
[11]	M. A. A. Hussein, M. A. Said, and A. A. Radwan, "Estimation of salinity profiles in the southeastern Mediterranean off the Egyptian coast". Journal of King Abdul-Aziz University (JKAU): Marine Science, (2011), (22), 79-95.
[12]	D. N. Fox, C. N. Barron, M. R. Carnes, M. Booda, G. Peggion, and J. V. Gurley, " The modular ocean data assimilation system". Oceanography, (2002), 15(1), 22–28.
[13]	W. C. Thacker, and L. Sindlinger, "Estimating salinity to complement observed temperature: 2. Northwestern Atlantic". Journal of Marine Systems, (2007), (65), 249-267.
[14]	K. T. Hjelmervik, and K. Hjelmervik, "Estimating temperature and salinity profiles using empirical orthogonal functions and clustering on historical measurements". Ocean Dynamics, (2013), (63), 809-821.
[15]	M. B. Gueye, A. Niang, S. Arnault, S. Thiria, and M. Crépon, "Neural approach to inverting complex system: Application to ocean salinity profile estimation from surface parameters". Computers & Geosciences, (2014), (72), 201-209.
[16]	CIESM website http://www.ciesm.org/marine/campaigns/sovietcruises.htm

Cite This Article

Plain Text BibTeX RIS

APA Style

Maged Mohamed Abdel Moneim Hussein. (2016). A Regression Model for Estimating Salinity in the South Eastern Mediterranean Sea. International Journal of Environmental Monitoring and Analysis, 4(2), 56-64. https://doi.org/10.11648/j.ijema.20160402.13

Copy | Download

ACS Style

Maged Mohamed Abdel Moneim Hussein. A Regression Model for Estimating Salinity in the South Eastern Mediterranean Sea. Int. J. Environ. Monit. Anal. 2016, 4(2), 56-64. doi: 10.11648/j.ijema.20160402.13

Copy | Download

AMA Style

Maged Mohamed Abdel Moneim Hussein. A Regression Model for Estimating Salinity in the South Eastern Mediterranean Sea. Int J Environ Monit Anal. 2016;4(2):56-64. doi: 10.11648/j.ijema.20160402.13

Copy | Download

@article{10.11648/j.ijema.20160402.13,
  author = {Maged Mohamed Abdel Moneim Hussein},
  title = {A Regression Model for Estimating Salinity in the South Eastern Mediterranean Sea},
  journal = {International Journal of Environmental Monitoring and Analysis},
  volume = {4},
  number = {2},
  pages = {56-64},
  doi = {10.11648/j.ijema.20160402.13},
  url = {https://doi.org/10.11648/j.ijema.20160402.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20160402.13},
  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.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - A Regression Model for Estimating Salinity in the South Eastern Mediterranean Sea
AU  - Maged Mohamed Abdel Moneim Hussein
Y1  - 2016/04/05
PY  - 2016
N1  - https://doi.org/10.11648/j.ijema.20160402.13
DO  - 10.11648/j.ijema.20160402.13
T2  - International Journal of Environmental Monitoring and Analysis
JF  - International Journal of Environmental Monitoring and Analysis
JO  - International Journal of Environmental Monitoring and Analysis
SP  - 56
EP  - 64
PB  - Science Publishing Group
SN  - 2328-7667
UR  - https://doi.org/10.11648/j.ijema.20160402.13
AB  - 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.
VL  - 4
IS  - 2
ER  -

Copy | Download

Author Information

Maged Mohamed Abdel Moneim Hussein

Marine Physics Laboratory, Division of Marine Environment, National Institute of Oceanography and Fisheries, Alexandria, Egypt

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Maged Mohamed Abdel Moneim Hussein. (2016). A Regression Model for Estimating Salinity in the South Eastern Mediterranean Sea. International Journal of Environmental Monitoring and Analysis, 4(2), 56-64. https://doi.org/10.11648/j.ijema.20160402.13

Copy | Download

ACS Style

Maged Mohamed Abdel Moneim Hussein. A Regression Model for Estimating Salinity in the South Eastern Mediterranean Sea. Int. J. Environ. Monit. Anal. 2016, 4(2), 56-64. doi: 10.11648/j.ijema.20160402.13

Copy | Download

AMA Style

Maged Mohamed Abdel Moneim Hussein. A Regression Model for Estimating Salinity in the South Eastern Mediterranean Sea. Int J Environ Monit Anal. 2016;4(2):56-64. doi: 10.11648/j.ijema.20160402.13

Copy | Download

@article{10.11648/j.ijema.20160402.13,
  author = {Maged Mohamed Abdel Moneim Hussein},
  title = {A Regression Model for Estimating Salinity in the South Eastern Mediterranean Sea},
  journal = {International Journal of Environmental Monitoring and Analysis},
  volume = {4},
  number = {2},
  pages = {56-64},
  doi = {10.11648/j.ijema.20160402.13},
  url = {https://doi.org/10.11648/j.ijema.20160402.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20160402.13},
  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.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - A Regression Model for Estimating Salinity in the South Eastern Mediterranean Sea
AU  - Maged Mohamed Abdel Moneim Hussein
Y1  - 2016/04/05
PY  - 2016
N1  - https://doi.org/10.11648/j.ijema.20160402.13
DO  - 10.11648/j.ijema.20160402.13
T2  - International Journal of Environmental Monitoring and Analysis
JF  - International Journal of Environmental Monitoring and Analysis
JO  - International Journal of Environmental Monitoring and Analysis
SP  - 56
EP  - 64
PB  - Science Publishing Group
SN  - 2328-7667
UR  - https://doi.org/10.11648/j.ijema.20160402.13
AB  - 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.
VL  - 4
IS  - 2
ER  -

Copy | Download