• Baltic Sea Hydrographic Commission, 2013: Baltic Sea Bathymetry Database Version 0.9.3. http://data.bshc.pro/#2/58.6/16.2.

  • Chen, D., A. J. Busalacchi, and L. M. Rothstein, 1994: The roles of vertical mixing, solar radiation, and wind stress in a model simulation of the sea surface temperature seasonal cycle in the tropical Pacific Ocean. J. Geophys. Res., 99, 20 34520 359, https://doi.org/10.1029/94JC01621.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • De Boyer Montégut, C., G. Madec, A. S. Fischer, A. Lazar, and D. Iudicone, 2004: Mixed layer depth over the global ocean: An examination of profile data and a profile-based climatology. J. Geophys. Res., 109, C12003, https://doi.org/10.1029/2004JC002378.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dong, S., J. Sprintall, S. T. Gille, and L. Talley, 2008: Southern ocean mixed-layer depth from Argo float profiles. J. Geophys. Res., 113, C06013, https://doi.org/10.1029/2006JC004051.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dzierzbicka-Głowacka, L., A. Nowicki, M. Janecki, B. Szymczycha, P. Piotrowski, P. Pieckiel, and G. Łukasiewicz, 2018: Structure of the FindFish Knowledge Transfer Platform. Fish. Aquat. Life, 26, 193197, https://doi.org/10.2478/aopf-2018-0021.

    • Search Google Scholar
    • Export Citation
  • Foltz, G. R., S. A. Grodsky, J. A. Carton, and M. J. McPhaden, 2003: Seasonal mixed layer heat budget of the tropical Atlantic Ocean. J. Geophys. Res., 108, 3146, https://doi.org/10.1029/2002JC001584.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grelowska, G., E. Kozaczka, and D. Witos-Okrasińska, 2018: Vertical temperature stratification of the Gulf of Gdansk water. 2018 Joint Conf. - Acoustics, Ustka, Poland, Institute of Electrical and Electronics Engineers, 16, https://doi.org/10.1109/ACOUSTICS.2018.8502387.

    • Search Google Scholar
    • Export Citation
  • Holte, J., and L. Talley, 2009: A new algorithm for finding mixed layer depths with applications to Argo data and subantarctic mode water formation. J. Atmos. Oceanic Technol., 26, 19201939, https://doi.org/10.1175/2009JTECHO543.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Janecki, M., D. Dybowski, J. Jakacki, A. Nowicki, and L. Dzierzbicka-Glowacka, 2021: The use of satellite data to determine the changes of hydrodynamic parameters in the Gulf of Gdańsk via Ecofish model. Remote Sens., 13, 3572, https://doi.org/10.3390/rs13183572.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kara, A. B., P. A. Rochford, and H. E. Hurlburt, 2000: An optimal definition for ocean mixed layer depth. J. Geophys. Res., 105, 16 80316 821, https://doi.org/10.1029/2000JC900072.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kara, A. B., A. J. Wallcraft, and H. E. Hurlburt, 2003: Climatological SST and MLD predictions from a global layered ocean model with an embedded mixed layer. J. Atmos. Oceanic Technol., 20, 16161632, https://doi.org/10.1175/1520-0426(2003)020<1616:CSAMPF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Karagali, I., J. Høyer, and C. Hasager, 2012: SST diurnal variability in the North Sea and the Baltic Sea. Remote Sens. Environ., 121, 159170, https://doi.org/10.1016/j.rse.2012.01.016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Leppäranta, M., and K. Myrberg, 2009: Topography and hydrography of the Baltic Sea. Physical Oceanography of the Baltic Sea, Springer, 4188, https://doi.org/10.1007/978-3-540-79703-6_3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Longhurst, A., 1995: Seasonal cycles of pelagic production and consumption. Prog. Oceanogr., 36, 77167, https://doi.org/10.1016/0079-6611(95)00015-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lorbacher, K., D. Dommenget, P. P. Niiler, and A. Köhl, 2006: Ocean mixed layer depth: A subsurface proxy of ocean-atmosphere variability. J. Geophys. Res., 111, C07010, https://doi.org/10.1029/2003JC002157.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lukas, R., and E. Lindstrom, 1991: The mixed layer of the western equatorial pacific ocean. J. Geophys. Res., 96, 33433357, https://doi.org/10.1029/90JC01951.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marshall, J., and F. Schott, 1999: Open-ocean convection: Observations, theory, and models. Rev. Geophys., 37, 164, https://doi.org/10.1029/98RG02739.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Masson, S., P. Delecluse, J.-P. Boulanger, and C. Menkes, 2002: A model study of the seasonal variability and formation mechanisms of the barrier layer in the eastern equatorial Indian Ocean. J. Geophys. Res., 107, 8017, https://doi.org/10.1029/2001JC000832.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Monterey, G., and S. Levitus, 1997: Seasonal variability of mixed layer depth for the World Ocean. NOAA Atlas NESDIS 14, 96 pp.

  • Morel, A., and J.-M. André, 1991: Pigment distribution and primary production in the western Mediterranean as derived and modeled from coastal zone color scanner observations. J. Geophys. Res., 96, 12 68512 698, https://doi.org/10.1029/91JC00788.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Noh, Y., C. J. Jang, T. Yamagata, P. C. Chu, and C.-H. Kim, 2002: Simulation of more realistic upper-ocean processes from an OGCM with a new ocean mixed layer model. J. Phys. Oceanogr., 32, 12841307, https://doi.org/10.1175/1520-0485(2002)032<1284:SOMRUO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Obata, A., J. Ishizaka, and M. Endoh, 1996: Global verification of critical depth theory for phytoplankton bloom with climatological in situ temperature and satellite ocean color data. J. Geophys. Res., 101, 20 65720 667, https://doi.org/10.1029/96JC01734.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Polovina, J. J., G. T. Mitchum, and G. T. Evans, 1995: Decadal and basin-scale variation in mixed layer depth and the impact on biological production in the central and north pacific, 1960–88. Deep-Sea Res. I, 42, 17011716, https://doi.org/10.1016/0967-0637(95)00075-H.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rak, D., and P. Wieczorek, 2012: Variability of temperature and salinity over the last decade in selected regions of the southern Baltic Sea. Oceanologia, 54, 339354, https://doi.org/10.5697/oc.54-3.339.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rao, R. R., R. L. Molinari, and J. F. Festa, 1989: Evolution of the climatological near-surface thermal structure of the tropical Indian Ocean: 1. Description of mean monthly mixed layer depth, and sea surface temperature, surface current, and surface meteorological fields. J. Geophys. Res., 94, 10 80110 815, https://doi.org/10.1029/JC094iC08p10801.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schneider, N., and P. Müller, 1990: The meridional and seasonal structures of the mixed-layer depth and its diurnal amplitude observed during the Hawaii-to-Tahiti Shuttle experiment. J. Phys. Oceanogr., 20, 13951404, https://doi.org/10.1175/1520-0485(1990)020<1395:TMASSO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Spall, M. A., R. A. Weller, and P. W. Furey, 2000: Modeling the three-dimensional upper ocean heat budget and subduction rate during the subduction experiment. J. Geophys. Res. Oceans, 105, 26 15126 166, https://doi.org/10.1029/2000JC000228.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sprintall, J., and D. Roemmich, 1999: Characterizing the structure of the surface layer in the Pacific Ocean. J. Geophys. Res., 104, 23 29723 311, https://doi.org/10.1029/1999JC900179.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thompson, R. O. R. Y., 1976: Climatological numerical models of the surface mixed layer of the ocean. J. Phys. Oceanogr., 6, 496503, https://doi.org/10.1175/1520-0485(1976)006<0496:CNMOTS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thomson, R. E., and I. V. Fine, 2003: Estimating mixed layer depth from oceanic profile data. J. Atmos. Oceanic Technol., 20, 319329, https://doi.org/10.1175/1520-0426(2003)020<0319:EMLDFO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weller, R. A., and A. J. Plueddemann, 1996: Observations of the vertical structure of the oceanic boundary layer. J. Geophys. Res., 101, 87898806, https://doi.org/10.1029/96JC00206.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, R.-H., and S. E. Zebiak, 2002: Effect of penetrating momentum flux over the surface boundary/mixed layer in a z-coordinate OGCM of the tropical pacific. J. Phys. Oceanogr., 32, 36163637, https://doi.org/10.1175/1520-0485(2002)032<3616:EOPMFO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 515 513 30
Full Text Views 93 92 10
PDF Downloads 110 108 11

A New Method for Thermocline and Halocline Depth Determination at Shallow Seas

Maciej JaneckiaEcohydrodynamics Laboratory, Physical Oceanography Department, Institute of Oceanology, Polish Academy of Sciences, Sopot, Poland

Search for other papers by Maciej Janecki in
Current site
Google Scholar
PubMed
Close
,
Dawid DybowskiaEcohydrodynamics Laboratory, Physical Oceanography Department, Institute of Oceanology, Polish Academy of Sciences, Sopot, Poland

Search for other papers by Dawid Dybowski in
Current site
Google Scholar
PubMed
Close
,
Daniel RakbObservational Oceanography Laboratory, Physical Oceanography Department, Institute of Oceanology, Polish Academy of Sciences, Sopot, Poland

Search for other papers by Daniel Rak in
Current site
Google Scholar
PubMed
Close
, and
Lidia Dzierzbicka-GlowackaaEcohydrodynamics Laboratory, Physical Oceanography Department, Institute of Oceanology, Polish Academy of Sciences, Sopot, Poland

Search for other papers by Lidia Dzierzbicka-Glowacka in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

This paper introduces a new method for finding the top of thermocline (TTD) and halocline (THD) depths that may become a powerful tool for applications in shallow marine basins around the world. The method calculates the moving average of the ocean vertical profile’s short-scale spatial variability (standard deviation) and then processes it to determine the potential depth at which temperature or salinity rapidly changes. The method has been calibrated using an extensive set of data from the ecohydrodynamic model EcoFish. As a result of the calibration, the values of the input parameters that allowed the correct determination of TTD and THD were established. It was confirmed by the validation carried out on the in situ profiles collected by the research vessel S/Y Oceania during statutory cruises in the southern Baltic Sea. The “MovSTD” algorithm was then used to analyze the seasonal variability of the vertical structure of the waters in Gdańsk Deep for temperature and salinity. The thermocline deepening speed was also estimated in the region analyzed.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Maciej Janecki, mjanecki@iopan.pl

Abstract

This paper introduces a new method for finding the top of thermocline (TTD) and halocline (THD) depths that may become a powerful tool for applications in shallow marine basins around the world. The method calculates the moving average of the ocean vertical profile’s short-scale spatial variability (standard deviation) and then processes it to determine the potential depth at which temperature or salinity rapidly changes. The method has been calibrated using an extensive set of data from the ecohydrodynamic model EcoFish. As a result of the calibration, the values of the input parameters that allowed the correct determination of TTD and THD were established. It was confirmed by the validation carried out on the in situ profiles collected by the research vessel S/Y Oceania during statutory cruises in the southern Baltic Sea. The “MovSTD” algorithm was then used to analyze the seasonal variability of the vertical structure of the waters in Gdańsk Deep for temperature and salinity. The thermocline deepening speed was also estimated in the region analyzed.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Maciej Janecki, mjanecki@iopan.pl

Supplementary Materials

    • Supplemental Materials (PDF 80.2 KB)
Save