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Novel metrics based on Biogeochemical Argo data to improve the model uncertainty evaluation of the CMEMS Mediterranean marine ecosystem forecasts

机译:基于生物地理ARGO数据的新型指标,提高CMEMS地中海海洋生态系统预测的模型不确定性评价

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摘要

The quality of the upgraded version of the Copernicus Marine Environment Monitoring Service (CMEMS) biogeochemical operational system of the Mediterranean Sea (MedBFM) is assessed in terms of consistency and forecast skill, following a mixed validation protocol that exploits different reference data from satellite, oceanographic databases, Biogeochemical Argo floats, and literature. We show that the quality of the MedBFM system has been improved in the previous 10 years. We demonstrate that a set of metrics based on the GODAE (Global Ocean Data Assimilation Experiment) paradigm can be efficiently applied to validate an operational model system for biogeochemical and ecosystem forecasts. The accuracy of the CMEMS biogeochemical products for the Mediterranean Sea can be achieved from basin-wide and seasonal scales to mesoscale and weekly scales, and its level depends on the specific variable and the availability of reference data, the latter being an important prerequisite to build robust statistics. In particular, the use of the Biogeochemical Argo floats data proved to significantly enhance the validation framework of operational biogeochemical models. New skill metrics, aimed to assess key biogeochemical processes and dynamics (e.g. deep chlorophyll maximum depth, nitracline depth), can be easily implemented to routinely monitor the quality of the products and highlight possible anomalies through the comparison of near-real-time (NRT) forecasts skill with pre-operationally defined seasonal benchmarks. Feedbacks to the observing autonomous systems in terms of quality control and deployment strategy are alsodiscussed.
机译:的哥白尼海洋环境监视服务(CMEMS)地中海(MedBFM)的生物地球化学业务系统的升级版的质量进行评估的一致性和预测技术人员而言,以下,它利用从卫星不同的基准数据的混合验证方案,海洋数据库,生物地球化学Argo浮筒,和文献。我们表明,MedBFM系统的质量在过去10年得到了改善。我们表明,一组基于所述GODAE(全球海洋数据同化试验)度量的范例可以有效地施加到验证的操作模型系统,用于生物地球化学和生态系统的预测。的精度CMEMS可以从全流域来实现生物地球化学产品为地中海和季节性秤到尺度的和每周秤,其水平取决于具体的变量和参考数据的可用性,后者是建立一个重要的先决条件强大的统计数据。特别是,使用生物地球化学的Argo的浮证明显著提升运营生物地球化学模型的验证框架数据。新的技能指标,目的是评估的关键生物地球化学过程和动力学(如深叶绿素最大深度,nitracline深度),可以轻松实现例行监测产品的质量,并强调通过近实时的比较可能的异常(NRT )预测具有预操作上定义季节性基准技能。反馈到观察自治系统中的质量控制和部署策略的术语alsodiscussed。

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