Deadline for abstract submission: 13 September 2023
While the increase of atmospheric CO2 from fossil fuel burning is the main driver of ocean acidification (OA), coastal processes (e.g., upwelling, river input, benthic production and respiration) can increase complexity. Local coastal processes can modulate or exacerbate OA from atmospheric CO2, and these processes occur on spatial scales that are not well represented in global climate models (GCMs). Additionally, projections rely mainly on chemical-physical variables with simplistic thresholds for the status and trends of biodiversity and ecosystem services. As a result, predictive information to support decisions facing coastal communities on OA impacts is largely lacking.
Ocean predictions and projections on local scales to support decisions require us to employ new technologies: digital twins, machine learning, high resolution predictions, observational data utilization, and integration of biological and ecological information.
This session highlights best practices for forecasting and providing localized projections, new approaches to address the computationally intense requirements of providing climate information at hyper-local scales, advancing the integration of biological and ecological information, innovative technologies that integrate autonomous real time observations and visualization of the output. We invite all approaches that deliver forecasts, projections of state, variability, phenology as well as novel ways of delivering data/knowledge to stakeholders.
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Ocean Sciences Meeting 2024. More information.
