The Bay of Bengal (BoB) exhibits a distinctive pattern of surface freshening primarily resulting from runoff originating from several major rivers and the monsoon precipitation. This freshening significantly modulates the spatial and temporal variations in the thermohaline structure, ultimately shaping the sound speed structure within this region. This study investigates the seasonal impact of river input on the sound speed structure of the BoB through two numerical simulations with and without river input using the Regional Ocean Modeling System (ROMS). The findings indicate that river inputs consistently reduce the surface sound speed across the domain throughout the year, with the most noticeable effect occurring in the northern part of BoB during the post-monsoon months of October and November. During this period, the surface variability is predominately driven by salinity variations induced by river inputs. In contrast, in the subsurface layers, the influence of reduced salinity becomes less pronounced with increasing depth, and the temperature modulations brought about by river inputs play a more important role. Freshening in the surface layers leads to the creation of a stratified barrier layer just below the mixed layer. Consequently, this results in the formation of warm temperature inversions in the subsurface layers, with cooling occurring beneath them. These phenomena contribute to variations in the sound speed, causing it to increase within the inversion layer and decrease below it. Notably, the sonic layer depth (SLD) is found to become shallower in the presence of river inputs during the post-monsoon and winter seasons in the northern BoB. The combination of enhanced vertical salinity gradients and subsurface temperature inversions significantly amplifies the vertical gradient of sound speed above the SLD. This, in turn, may lead to the development of more robust surface ducts and the expansion of shadow zones beneath the SLD.

Abstract: We begin with a motivation for the challenges faced in weather and climate modeling and then describe why we need special time-integration methods in order to evolve the governing equations forward in time. A quick review of element-based Galerkin (EBG) methods that we use in our models will be given followed by a description of the contravariant form of the discretization that then simplifies the application of horizontally explicit vertically implicit (HEVI) time-integrators regardless of whether we are solving regional or global models. This talk is motivated by my group and collaborators’ research in building operational weather prediction models as well as advancing the field for application in climate, space weather, and ocean dynamics. A list of publications on these topics can be found at: https://frankgiraldo.wixsite.com/mysite/publications

Biography: Francis Giraldo is a distinguished professor in the Department of Applied Mathematics at the Naval Postgraduate School in Monterey, California. He is in the Scientific Computing group and mostly teaches and performs research in this area. For example, he teaches Numerical Linear Algebra, Numerical Analysis, Galerkin Methods, and Scientific Computing. He is also an Adjunct Professor of Applied Mathematics at the University of California at Santa Cruz. His research area is in numerical methods for partial differential equations (PDEs). Although he mainly works on nonlinear systems of hyperbolic equations, he also works on elliptic and parabolic PDEs.