Assessing the long-term physical-biogeochemical interactions in the North Indian Ocean using a coupled relocatable model

Jardine, Jennifer; Katavouta, Anna ORCID: https://orcid.org/0000-0002-1587-4996; Partridge, Dale; Polton, Jeff ORCID: https://orcid.org/0000-0003-0131-5250; Holt, Jason ORCID: https://orcid.org/0000-0002-3298-8477; Wakelin, Sarah ORCID: https://orcid.org/0000-0002-2081-2693. 2021 Assessing the long-term physical-biogeochemical interactions in the North Indian Ocean using a coupled relocatable model. In: EGU General Assembly 2021, Online, 19-30 April 2021.

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Abstract/Summary

The Indian Ocean is a dynamic region that is heavily influenced by immense freshwater runoff, extreme meteorological events and the seasonal reversal of monsoonal currents. Providing essential resources for over one-third of the global population, the Northern Indian Ocean is a key area of research: increased freshwater run-off, low overturning velocities and high air-sea fluxes result in the region being highly susceptible to climate fluctuations, and execess nutrients, particularly nitrates accumulated through agricultural run-off, directly influence marine biogeochemical cycles. The South Asia Nitrogen Hub (SANH) is a GCRF project designed to assess, monitor and predict the physical and biogeochemical response of the Northern Indian Ocean to such anthropogenic changes. To address key questions in SANH, a relocatable physical-biogeochemical (NEMO-ERSEM) was configured across the region, which includes the Eastern Arabian Sea and the Bay of Bengal. A 22-year hindcast run (1993-2015) at ~11km resolution allows the physical-biogeochemical processes (including from mesoscale eddies, extreme meteorological events and varying runoff) to be viewed at scale that is otherwise impossible with observational campaigns. In conjunction with the large-scale model domain, 6 smaller high-resolution (~1-2km) coastal models were configurated around the Indian subcontinent, allowing a more focussed view at processes that directly impact coastal populations. Here, we will present initial results from the large-scale hindcast run, the coastal regions, and explore the advantages and caveats of relocatable modelling.

Item Type:	Publication - Conference Item (Paper)
Digital Object Identifier (DOI):	10.5194/egusphere-egu21-9706
Date made live:	19 May 2021 09:47 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/530315

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