Skip to main content
SpringerLink
Log in

Modified Technique for Calculating the Parameters of Climatic Variability of Upwelling by Thermal Index

  • PHYSICAL BASES AND METHODS OF STUDYING THE EARTH FROM SPACE
  • Published:
Izvestiya, Atmospheric and Oceanic Physics Aims and scope Submit manuscript

Abstract

A modified technique for calculating the amplitude-phase characteristics of the seasonal cycle and long-term trends in the intensity of upwelling is discussed based on an analysis of the minimum (maximum in the absolute value) values of the thermal upwelling index (TUI). The TUI is calculated as the difference in satellite sea surface temperature (SST) between the coastal and offshore zones in the areas of large-scale oceanic upwelling. The proposed technique is used to calculate the climatic variability parameters of the Eastern Boundary Upwelling Systems (EBUS’s). The seasonal variations of the TUI calculated in this approach are in better agreement with the intra-annual variability of the upward motions of the wind origin than changes in the TUI values averaged over climatic masks. The long-term TUI trends obtained by using the modified method are more significant than those calculated in climatic masks and confirm the intensification of upwelling in the last ~35 years.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.

Similar content being viewed by others

REFERENCES

  1. Bakun, A., Global climate change and intensification of coastal ocean upwelling, Science, 1990, vol. 247, pp. 198–201. https://doi.org/10.1126/science.247.4939.198

    Article  Google Scholar 

  2. Bakun, A., Black, B.A., Bograd, S.J., García-Reyes, M., Miller, A.J., Rykaczewski, R.R., et al., Anticipated effects of climate change on coastal upwelling ecosystems, Curr. Clim. Change Rep., 2015, vol. 1, pp. 85–93. https://doi.org/10.1007/s40641-015-0008-4

    Article  Google Scholar 

  3. Belmadani, A., Echevin, V., Codron, F., Takahashi, K., and Junquas, C., What dynamics drive future wind scenarios for coastal upwelling off Peru and Chile?, Clim. Dyn., 2014, vol. 43, nos. 7–8, pp. 1893–1914.

    Article  Google Scholar 

  4. Cade, B. and Noon, B., A gentle introduction to quantile regression for ecologists, Front. Ecol. Environ., 2003, vol. 1, pp. 412–420. https://doi.org/10.1890/1540-9295(2003)001[0412:AGITQR]2.0.CO;2

    Article  Google Scholar 

  5. Carr, M.E., Estimation of potential productivity in Eastern Boundary Currents using remote sensing, Deep-Sea Res., Part II, 2002, vol. 49, nos. 1–3, pp. 59–80.

    Article  Google Scholar 

  6. Carr, M.E. and Kearns, E.J., Production regimes in four Eastern Boundary Current systems, Deep-Sea Res., Part II, 2003, vol. 50, nos. 22–26, pp. 3199–3221.

    Article  Google Scholar 

  7. Chavez, F.P. and Messie, M., A comparison of eastern boundary upwelling ecosystems, Prog. Oceanogr., 2009, vol. 83, nos. 1–4, pp. 80–96. https://doi.org/10.1016/j.pocean.2009.07.032

    Article  Google Scholar 

  8. Chelton, D.B., deSzoeke, R.A., Schlax, M.G., El Naggar, K., and Siwertz, N., Geographical variability of the first baroclinic Rossby radius of deformation, J. Phys. Oceanogr., 1998, vol. 28, no. 3, pp. 433–460. https://doi.org/10.1175/1520-0485(1998)028<0433:GVOTFB>2.0.CO;2

    Article  Google Scholar 

  9. García-Reyes, M., Sydeman, W.J., Schoeman, D.S., Ry-kaczewski, R.R., Black, B.A., Smit, A.J., and Bograd, S.J., Under pressure: Climate change, upwelling, and eastern boundary upwelling ecosystems, Front. Mar. Sci., 2015, vol. 2, id 109. https://doi.org/10.3389/fmars.2015.00109

  10. Gill, A., Atmosphere–Ocean Dynamics, London: Academic, 1982; Moscow: Mir, 1986.

  11. Huyer, A., Coastal upwelling in the California current system, Prog. Oceanogr., 1983, pp. 259–284. https://doi.org/10.1016/0079-6611(83)90010-1

  12. IPCC, 2014: Climate Change 2014: Synthesis Report., Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Pachauri, R.K. and Meyer, L.A., Eds., Geneva: IPCC, 2014.

    Google Scholar 

  13. Koenker, R., Quantile Regression, Cambridge: Cambridge Univ. Press, 2005.

    Book  Google Scholar 

  14. Koenker, R. and Bassett, G., Regression quantiles, Econometrica, 1978, vol. 46, no. 1, pp. 33–50.

    Article  Google Scholar 

  15. Koenker, R. and Hallock, K., Quantile regression, J. Econ. Perspect., 2001, vol. 15, pp. 143–156.

    Article  Google Scholar 

  16. Pauly, D. and Christensen, V., Primary production required to sustain global fisheries, Nature, 1995, vol. 374, pp. 255–257. https://doi.org/10.1038/374255a0

    Article  Google Scholar 

  17. Philander, S.G., El Niño, La Niña and the Southern Oscillation, San Diego: Academic Press, 1990.https://doi.org/10.1126/science.248.4957.904

    Book  Google Scholar 

  18. Polonsky, A.B. and Serebrennikov, A.N., On the change in the ocean surface temperature in the Benguela upwelling region. Part I: Season cycle, Izv., Atmos. Ocean. Phys., 2019, vol. 55, no. 9, pp. 1050–1059. https://doi.org/10.1134/S0001433819090391

    Article  Google Scholar 

  19. Polonsky, A.B. and Serebrennikov, A.N., On the change in the sea surface temperature in the Benguela Upwelling Region: Part II. Long-term tendencies, Izv., Atmos. Ocean. Phys., 2020a, vol. 56, no. 9, pp. 970–978. https://doi.org/10.1134/S0001433820090200

    Article  Google Scholar 

  20. Polonsky, A.B. and Serebrennikov, A.N., Intensification of eastern boundary upwelling systems in the Atlantic and Pacific oceans, Russ. Meteorol. Hydrol., 2020b, vol. 45, no. 5, pp. 422–429.

    Article  Google Scholar 

  21. Seabold, S. and Perktold, J., Statsmodels: Econometric and statistical modeling with python, in Proceedings of the 9th Python in Science Conference, 2010. http://conference. scipy.org/proceedings/scipy2010/pdfs/seabold.pdf.

  22. Serebrennikov, A.N., An improved technique for the retrieval of coastal upwelling indices from satellite data, Sovrem. Probl. Distantsionnogo Zondirovaniya Zemli Kosmosa, 2018, vol. 15, no. 5, pp. 44–51.

    Article  Google Scholar 

  23. Upwelling: Mechanisms, Ecological Effects and Threats to Biodiversity, Fischer, W.E. and Green, A.B., Eds., Nova Sci. Publ., 2013, pp. 59–76.

    Google Scholar 

Download references

ACKNOWLEDGMENTS

We are grateful to an anonymous reviewer for their encouraging report and constructive remarks.

Funding

This study was carried out as part of State Task no. 0012-2019-0002 (“Basic Studies of the Processes in a Climatic System that Determine the Spacetime Variability of the Natural Environment of Global and Regional Scales.”)

Author information

Authors and Affiliations

  1. Institute of Natural and Technical Systems, Sevastopol, Russia

    A. B. Polonsky & A. N. Serebrennikov

Authors
  1. A. B. Polonsky
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. N. Serebrennikov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. B. Polonsky.

Ethics declarations

The authors declare that they have no conflicts of interest.

Additional information

Translated by M. Shmatikov

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Polonsky, A.B., Serebrennikov, A.N. Modified Technique for Calculating the Parameters of Climatic Variability of Upwelling by Thermal Index. Izv. Atmos. Ocean. Phys. 57, 1137–1145 (2021). https://doi.org/10.1134/S0001433821090590

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0001433821090590

Keywords:

Search

Navigation