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Observing System Evaluation Based on Ocean Data Assimilation and Prediction Systems: On-going Challenges and Future Vision for Designing/Supporting Ocean Observational Networks

机译:基于海洋数据同化和预报系统的观测系统评估:设计/支持海洋观测网络的挑战和未来远景

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This paper demonstrates the value of Observing System Evaluation (OS-Eval) efforts which have been made or are ongoing to contribute to observing system review and design with the support of Ocean Data Assimilation and Prediction (ODAP) communities such as GODAE OceanView and CLIVAR-GSOP, by highlighting examples that illustrate the potential of the related OS-Eval methodologies and recent achievements. For instance, Observing System Experiment (OSE) studies illustrate the impacts of the severe decrease in the number of TAO buoys during 2012-2014 and TRITON buoys since 2013 on ODAP system performance. Multi-system evaluation of the impacts of assimilating satellite sea surface salinity data based on OSEs has been performed to demonstrate the need to continue and enhance satellite salinity missions. Impacts of underwater gliders have been assessed using Observing System Simulation Experiments (OSSEs) to provide guidance on effective coordination of the western North Atlantic observing system elements. OSSEs are also being performed under H2020 AtlantOS project with the goal to enhance and optimize the Atlantic in-situ networks. Potential of future satellite missions of wide-swash altimetry and surface ocean currents monitoring is explored through OSSEs and evaluation of Degrees of Freedom for Signal (DFS). Forecast Sensitivity Observation Impacts (FSOI) are routinely evaluated for monitoring the ocean observation impacts in the US Navy’s ODAP system. Perspective on the extension of OS-Eval to the deep ocean, polar regions, coupled data assimilation, and biogeochemical applications are also presented. Based on the examples above, we identify the limitations of OS-Eval, indicating that the most significant limitation is reduction of robustness and reliability of the results due to their system-dependency. Inability of performing evaluation in near real time is also critical. A strategy to mitigate the limitation and to strengthen the impact of evaluations is discussed. In particular, we emphasize the importance of collaboration within the ODAP community for multi-system evaluation and communication with ocean observational communities on the design of OS-Eval, required resources, and effective distribution of the results. Finally, we recommend to further develop OS-Eval activities at international level with the support of the international ODAP (e.g., OceanPredict and CLIVAR-GSOP) and observational communities.
机译:本文展示了在海洋数据同化和预测(ODAP)社区(例如GODAE OceanView和CLIVAR-)的支持下,已经或正在进行的有助于观测系统审查和设计的观测系统评估(OS-Eval)工作的价值。 GSOP,着重举例说明了相关OS-Eval方法的潜力和最新成就。例如,观测系统实验(OSE)研究表明,2012-2014年期间TAO浮标和2013年以来TRITON浮标数量急剧减少对ODAP系统性能的影响。已经进行了基于OSE的同化卫星海面盐度数据影响的多系统评估,以证明需要继续和增强卫星盐度任务。水下滑翔机的影响已使用观测系统模拟实验(OSSE)进行了评估,以为北大西洋西部观测系统要素的有效协调提供指导。 HSE AtlantOS项目也正在执行OSSE,其目标是增强和优化大西洋现场网络。通过OSSE和信号自由度(DFS)的评估,探索了未来进行大范围冲高测星和地面海流监测的卫星任务的潜力。常规评估预报敏感性观测影响(FSOI),以监视美国海军ODAP系统中的海洋观测影响。还介绍了将OS-Eval扩展到深海,极地地区,耦合数据同化和生物地球化学应用的观点。根据上面的示例,我们确定了OS-Eval的局限性,这表明最重要的局限性是由于系统依赖性而导致结果的健壮性和可靠性下降。无法实时执行评估也很关键。讨论了减轻限制和增强评估影响的策略。特别是,我们强调了ODAP社区内部进行协作的重要性,以进行多系统评估并与海洋观测社区就OS-Eval的设计,所需资源以及结果的有效分配进行沟通。最后,我们建议在国际ODAP(例如OceanPredict和CLIVAR-GSOP)和观测界的支持下,进一步在国际一级开展OS-Eval活动。

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