Application of Ocean Colour Monitor chlorophyll and AVHRR SST for fishery forecast: Preliminary validation results off Gujarat coast, northwest coast of India

Abstract

Quantitative analysis of Sea Surface Temperature (SST) and chlorophyll improve our understanding of circulation and distribution of phytoplankton population in water masses. In this study near synchronous IRS P4 Ocean Colour Monitor (OCM) derived chlorophyll and NOAA AVHRR derived SST are used for exploring fishery resources. Ocean Color Monitor data were atmospherically corrected using long wavelength approach. Ocean Chlorophyll – 2 (OC2) bio-optical algorithm was applied to corrected radiance to calculate chlorophyll concentration. Multi Channel Sea Surface Temperature (MCSST) approach was adopted for estimation of SST from split window of NOAA AVHRR. Both data sets were geometrically corrected and registered with master image of north west coast of India so as to generate geo-coded chlorophyll and SST images. Sea surface temperature contours generated and overlaid on chlorophyll images to generate composite images. These composite images were interpreted for generating experimental fishery forecast along the Gujarat coast. Different types of the oceanic features like, coastal fronts, fringe fronts, rings, mushrooms, meanders and features shaped as tongue and mushroom, jet etc. were selected for forecast. The information was disseminated to Porbandar for validation. Gill-netters were used for experimental fishing. Suggested areas were located using Global Positioning System (GPS). The feedback received from fishing sites was analyzed. The catch per gill net operation was normalised and compared with month wise normal catch available around Porbandar. About 2-3 fold increase in the catch in Potential Fishing Zones (PFZ) area was observed. The frontal positions in chlorophyll image coincide with temperature boundaries at some locations. This coincidence indicates that physical and bio-chemical processes are closely coupled at these locations and can be used for identification of Potential Fishing Zones (PFZs).