Abstract

Coastal Upwelling, the upward flux of nutrient-rich waters into the euphotic layer, is associated with remarkable phytoplankton blooms, which form the base of the marine food web. In addition this entrainment of cold deeper waters to the surface, leads to sea surface temperature (SST) cooling that can also be determined from satellite observations of coastal SST gradients (often resulting in thermal fronts). Thermal fronts, (especially in high chlorophyll regions of the ocean,) are typically associated with significant biological activity.Thus, the detection of potential fishing zones (PFZs) typically involves the identification of fronts from satellite or model SST and Chl-a data. The western Bay of Bengal region presents some unique challenges with regard to the characterization and detection of PFZs based on these satellite data alone. Namely, the presence of clouds during southwest monsoon, (the season associated with the largest fish catches) limits the availability of infrared and visible data necessary for the estimation of high resolution SST and Chl-a. This difficulty is usually circumvented by using modelled SST and Chl-a data, which unfortunately illustrate significant disagreements with the corresponding observational datasets, especially for fronts with low persistence. Coastal upwelling along the east coast of India is seasonal and driven by southwesterly winds in the pre-monsoon (March – May) and earlier half of monsoon (June – July.)  We have previously characterized the seasonal variability of this system based on the near-shore SST gradient (represented in terms of an SST based upwelling index UISST.) In addition to this the second complex empirical orthogonal function of SSHA was also observed to consist of negative coastal anomalies that are strongly correlated with the local alongshore windstress (AWS) (which is considered the wind based proxy upwelling index), the driver of coastal upwelling (Ray et al, 2022.) This study includes a multiscale analysis of the association between the generation of SST fronts or PFZs and the proxies of coastal upwelling (such as UISST, AWS, SSHA reconstructed from the second EOF mode.) e.g. figure 1 illustrates the occurrence of high frontal probability indices (FPIs) along a part of the coast previously identified to be a local wind-driven coastal upwelling system (Ray et al, 2022,) while figure 2 illustrates a close agreement (correlation coefficient = 85%) between the seasonally filtered SST-based upwelling index and the FPI around one coastal point. An improved understanding of the role of coastal upwelling in the generation of PFZs is potentially of great societal importance as it can enable the development of methods of detecting/forecasting the probability of formation of PFZs based on surface wind and SSHA observations which are not affected by the presence of clouds.Figure 1Figure 2 Reference:Ray, S., Swain, D., Ali, M. M., & Bourassa, M. A. (2022). Coastal Upwelling in the Western Bay of Bengal: Role of Local and Remote Windstress. Remote Sensing, 14(19), 4703.

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