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Earth system models for regional environmental management of red tide: Prospects and limitations of current generation models and next generation development
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Earth system models for regional environmental management of red tide: Prospects and limitations of current generation models and next generation development
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Journal Article
Earth system models for regional environmental management of red tide: Prospects and limitations of current generation models and next generation development
2022
Overview
Earth system models (ESMs) serve as a unique research infrastructure for quality climate services, yet their application for environmental management at regional scale has not yet been fully explored. The unprecedented resolution and model fidelity of the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations, especially of the High-Resolution Model Intercomparison Project (HighResMIP) focusing on regional phenomena, offer opportunities for such applications. This article presents the first venture into using the HighResMIP simulations to tackle a regional environmental issue, the Florida Red Tide. This is a harmful algae bloom caused by the dinoflagellate Karenia brevis, a toxic single-celled microscopic protist. We use CMIP6 historical simulations to establish a causal agreement between the position of Loop Current, a warm ocean current that moves into the Gulf of Mexico, and the occurrence of K. brevis blooms on the Western Florida shelf. Results show that the high-resolution ESMs are capable of simulating the phenomena of interest (i.e., Loop Current) at the regional spatial scale with generally adequate data-model agreement in the context of the relation between Loop Current and red tide. We use this case study to elaborate on the prospects and limitations of using publicly available CMIP data for regional environmental management. We highlight the current gaps and the developmental needs for the next generation ESMs, and discuss the role of stakeholder participation in future ESMs development to facilitate the translation of scientific understanding to better inform decision-making of regional environmental management.
