Predicting the ocean state in a reliable and interoperable way, while ensuring high-quality products, requires forecasting systems that synergistically combine science-based methodologies with advanced technologies for timely, user-oriented solutions. Achieving this objective necessitates the adoption of best practices when implementing ocean forecasting services, resulting in the proper design of system components and the capacity to evolve through different levels of complexity. The vision of OceanPrediction Decade Collaborative Center, endorsed by the UN Decade of Ocean Science for Sustainable Development 2021-2030, is to support this challenge by developing a “predicted ocean based on a shared and coordinated global effort” and by working within a collaborative framework that encompasses worldwide expertise in ocean science and technology. To measure the capacity of ocean forecasting systems, the OceanPrediction Decade Collaborative Center proposes a novel approach based on the definition of an Operational Readiness Level (ORL). This approach is designed to guide and promote the adoption of best practices by qualifying and quantifying the overall operational status. Considering three identified operational categories - production, validation, and data dissemination - the proposed ORL is computed through a cumulative scoring system. This method is determined by fulfilling specific criteria, starting from a given base level and progressively advancing to higher levels. The goal of ORL and the computed scores per operational category is to support ocean forecasters in using and producing ocean data, information, and knowledge. This is achieved through systems that attain progressively higher levels of readiness, accessibility, and interoperability by adopting best practices that will be linked to the future design of standards and tools. This paper discusses examples of the application of this methodology, concluding on the advantages of its adoption as a reference tool to encourage and endorse services in joining common frameworks.
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Larval dispersal and juvenile survival are crucial in determining variation in recruitment, stock size and adult distribution of commercially important fish. This study investigates the dispersal of early-life stages of common sole (Solea solea L.) in the southern North Sea, both empirically and through modeling. Age at different life-history events of juvenile flatfish sampled along the coasts of Belgium, the Netherlands and the United Kingdom in 2013, 2014 and 2016, was determined through the counting of daily growth rings in the otoliths. Juveniles captured between August and October were estimated to be on average 140 days old with an average pelagic larval duration of 34 days. The hatching period was esti- mated between early April and mid-May followed by arrival and settlement in the nurseries between May and mid-June. Growth rates were higher off the Belgian coast than in the other nursery areas, especially in 2013, possibly due to a post-settlement differentiation. Empirical pelagic larval duration and settlement distributions were compared with the L AR- VAE &C O larval dispersal model, which combines local hydrodynamics in the North Sea with sole larval behavior. Yearly predicted and observed settlement matched partially, but the model estimated a longer pelagic phase. The observations fitted even better with the mod- elled average (1995–2015) distribution curves. Aberrant results for the small juvenile sole sampled along the UK coast in March 2016, led to the hypothesis of a winter disruption in the deposition of daily growth rings, potentially related to starvation and lower food availabil- ity. The similarities between measured and modelled distribution curves cross-validated both types of estimations and accredited daily ageing of juveniles as a useful method to cali- brate biophysical models and to understand early-life history of fish, both important tools in support of efficient fisheries management strategies.
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RBINS Staff Publications 2021