Paper
8 December 2006 Estimation of upper ocean heat content from remote sensing observations in the Arabian Sea
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Abstract
In this paper, we attempted to estimate the upper ocean heat content from Sea Surface Height Anomaly (SSHA), Sea Surface Temperature (SST) and Wind Stress Curl (WSC) obtained from satellite observations through Artificial Neural Networks approach. For this purpose, we analyzed the monthly heat content derived from 3D-model, SSHA, SST and WSC during 2000-2003. Due to non availability of Argo profiles at all locations during all the seasons, estimation of heat content is not possible at different time scales. 3D-model derived heat content is validated with Argo heat content during 2003. We have developed a model for the Arabian Sea to estimate upper ocean heat content, with a standard deviation error of 0.05E+09 J/m2. In estimating the Heat Content (HC) we also studied the effect of each parameter through ANN model.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
P. S. V. Jagadeesh and M. M. Ali "Estimation of upper ocean heat content from remote sensing observations in the Arabian Sea", Proc. SPIE 6404, Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions, 64041C (8 December 2006); https://doi.org/10.1117/12.699319
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KEYWORDS
Remote sensing

Data modeling

Error analysis

3D modeling

Alternate lighting of surfaces

Satellites

Statistical analysis

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