Articles | Volume 16, issue 1
https://doi.org/10.5194/esd-16-91-2025
https://doi.org/10.5194/esd-16-91-2025
Research article
 | 
15 Jan 2025
Research article |  | 15 Jan 2025

Estimating ocean heat content from the ocean thermal expansion parameters using satellite data

Vijay Prakash Kondeti and Shanmugam Palanisamy

Related authors

A semi-analytical model for diffuse reflectance in marine and inland waters
J. D. Pravin, P. Shanmugam, and Y.-H. Ahn
Ocean Sci. Discuss., https://doi.org/10.5194/osd-12-1893-2015,https://doi.org/10.5194/osd-12-1893-2015, 2015
Revised manuscript not accepted
Modelling of underwater light fields in turbid and eutrophic waters: application and validation with experimental data
B. Sundarabalan and P. Shanmugam
Ocean Sci., 11, 33–52, https://doi.org/10.5194/os-11-33-2015,https://doi.org/10.5194/os-11-33-2015, 2015
Short summary
A robust method for removal of glint effects from satellite ocean colour imagery
R. K. Singh and P. Shanmugam
Ocean Sci. Discuss., https://doi.org/10.5194/osd-11-2791-2014,https://doi.org/10.5194/osd-11-2791-2014, 2014
Revised manuscript not accepted
Short summary
An optical model for deriving the spectral particulate backscattering coefficients in oceanic waters
S. P. Tiwari and P. Shanmugam
Ocean Sci., 9, 987–1001, https://doi.org/10.5194/os-9-987-2013,https://doi.org/10.5194/os-9-987-2013, 2013

Cited articles

Ali, M. M., Jagadeesh, P. S. V., Lin, I. I., and Hsu, J. Y.: A neural network approach to estimate tropical cyclone heat potential in the Indian Ocean, IEEE Geosci. Remote S., 9, 1114–1117, https://doi.org/10.1109/LGRS.2012.2190491, 2012. 
Baxter, J. M.: Explaining Ocean Warming: Causes, scale, effects and consequences, edited by: Laffoley, D. and Baxter, J. M., IUCN, International Union for Conservation of Nature, https://doi.org/10.2305/IUCN.CH.2016.08.en, 2016. 
Beech, N., Rackow, T., Semmler, T., Danilov, S., Wang, Q., and Jung, T.: Long-term evolution of ocean eddy activity in a warming world, Nat. Clim. Change, 12, 910–917, https://doi.org/10.1038/s41558-022-01478-3, 2022. 
Download
Short summary
Ocean heat content (OHC) is an essential climate variable and is highly correlated with thermosteric sea level rise (TSL). In this study, ocean-thermal-expansion-based artificial neural network models were developed and validated to estimate TSL and, subsequently, OHC at 17 depths from the surface to 700 m. These models can accurately predict TSL and OHC for the given input data on sea surface temperature and sea surface salinity from any source.
Altmetrics
Final-revised paper
Preprint