Integrative Analysis of AltiKa-SSHa, MODIS-SST, and OCM-Chlorophyll Signatures for Fisheries Applications

Abstract

The study focused on integrative signature analysis of synchronous chlorophyll concentrations (CC), Sea Surface Temperature (SST), and Sea Surface Height anomaly (SSHa) for fisheries applications. CC and SST were derived from IRS-OCM and MODIS, respectively, and SSHa was derived from SARAL-AltiKa, AVISO Ssalto/ Duacs, and TOPEX/Poseidon. Spatial profiles were generated to visualize patterns of variability in signatures, their distribution, persistence, and interrelationship. The patterns of SST and SSHa signatures are co-varying in many cases indicating linearly related and the correlation was r D 0.79, whereas chlorophyll and SST/SSHa profiles are inversely related and the correlation was r D ¡0.82 and ¡0.73, respectively. Time series analysis of these variables shows areas of negative SSHa consist of high CC and relatively low SST. This suggests that negative SSHa areas consist of dense nutrient rich water and can be used as an indicator of enhanced biological production sites. Fishing operations data were procured from Fishery Survey of India (FSI). Fish catch in terms of catch per unit efforts (CPUE) were related with signatures of variables. High CPUE locations/contours were found in the vicinity of low SSHa/SST and high CC consisting waters.

A Hybrid Deep Learning Model for the Bias Correction of SST Numerical Forecast Products Using Satellite Data

“…SST is an important physical quantity for global climate studies [1], marine ecosystem studies, and related applications. The forecast accuracy of SST is essential for marine disaster prevention, navigation, ocean fishery [2], and other ocean-related cases. SST prediction methods can be classified into two major categories [3].…”

An introduction to the ‘Oceans and Society: Blue Planet’ initiative

“…Ocean biological and biodiversity observations are critical in monitoring the health of and changes to ocean and coastal ecosystems and biodiversity, and are required to gauge progress towards the Aichi biodiversity targets (Andrefouet et al 2008;CBD 2010CBD , 2014Miloslavich et al 2017). Ocean observations are also important in managing fisheries and aquaculture (Saitoh et al 2011;Solanki et al 2015;Hazen et al 2018).…”