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The role of biogeochemical processes in controlling LMR-relevant properties in an Eastern Bering Sea climate-to-fish modeling framework

This project aims to better constrain uncertainty related to local biogeochemistry when down-scaling climate model output to predict changes in primary and secondary production of the Eastern Bering Sea (EBS). Due to its economic and cultural importance, changes in the EBS ecosystem have prompted a series of contemporary research efforts to advance our understanding of key ecosystem processes, their relationship to the physical environment, and their probable response to future changes in the global climate. Central to these research efforts has been the development of a dynamical downscaling framework to connect drivers from global Earth System Models (ESMs) to an ensemble of ecosystem models in the EBS via a10-km horizontal resolution Regional Ocean Modeling System domain (Bering10K ROMS). To provide credible Living Marine Resource (LMR) predictions, a model must capture not only the physical dynamics of a system, but also local biogeochemical processes; these processes
are poorly constrained by data but exert tight controls over the simulated levels of primary and
secondary production.

To better quantify the biophysical linkages within this Bering Sea modeling framework, and the sensitivity of regional climate projections to the assumptions inherent within the bio-geochemical module, we propose to conduct a biogeochemical model intercomparison for the Bering Sea. Our model intercomparison will couple four existing biogeochemical models, all with contrasting but equally justifiable representations of the lower trophic level dynamics of the Bering Sea, to an identical hydrodynamic model forced with historical atmospheric and lateral ocean boundary conditions. This approach will allow us to better quantify the inter-model uncertainty range, and isolate uncertainty that can be attributed to biogeochemical model structure and parameterization as opposed to variations in ocean model hydrodynamics and forcing. By analyzing which physical drivers elicit a consistent response across model frameworks, versus those whose effect on LMR-relevant metrics are variable, we can better identify which physical drivers lead to outcomes that are robust to biogeochemical uncertainty. Our proposed research specifically addresses focus areas A and C in Competition 4, namely, to identify key climate/oceanic processes that affect ocean biogeochemistry of relevance to fisheries and other LMRs, and to improve modeling of climate-ocean predictability pathways. It will allow explicit quantification of variability associated with an often-overlooked aspect of climate-to-fish modeling: the lower trophic level biogeochemical models that “translate” climate drivers into LMR-relevant indices. We believe this work will lead to more reliable predictions within the Bering Sea modeling framework, which has and continues to support a variety of research projects to predict climate effects on socio-ecological components of the
Bering Sea ecosystem. In a larger context, it will inform similar applications using regional
downscaling of climate models to predict changes in living marine resources. Ultimately this
work promotes climate-resilient fisheries and coastal communities in the Bering Sea through
integrated climate-informed decision making and ecosystem-based fisheries management. As
such, it is aligned with MAPP’s focus on “coupling, integration, and application of Earth System models and analyses across NOAA”, and NOAA’s long term goals of providing service to climate adaptation and mitigation, healthy oceans, and resilient coastal communities and Economies.

Climate Risk Area: Marine Ecosystems

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