Ocean Reanalyses: Recent Advances and Unsolved Challenges
Ocean Reanalyses: Recent Advances and Unsolved Challenges
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DOI：
10.3389/fmars.2019.00418
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发表时间：
2019-07
影响因子：
3.7
通讯作者：
A. Storto;A. Álvera-Azcárate;M. Balmaseda;A. Barth;M. Chevallier;F. Counillon;C. Domingues;M. Drévillon;Y. Drillet;G. Forget;G. Garric;K. Haines;F. Hernandez;D. Iovino;L. Jackson;J. Lellouche;S. Masina;M. Mayer;M. Mayer;P. Oke;S. Penny;A. Peterson;Chunxue Yang;H. Zuo
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文献类型：
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作者：
A. Storto;A. Álvera-Azcárate;M. Balmaseda;A. Barth;M. Chevallier;F. Counillon;C. Domingues;M. Drévillon;Y. Drillet;G. Forget;G. Garric;K. Haines;F. Hernandez;D. Iovino;L. Jackson;J. Lellouche;S. Masina;M. Mayer;M. Mayer;P. Oke;S. Penny;A. Peterson;Chunxue Yang;H. Zuo
海洋再分析将海洋模式、大气强迫通量和使用数据同化的观测结合起来，给出海洋的四维描述。随着时间的推移，重新评估其可靠性的方法得到了改进，使重新分析成为气候服务中的一个重要工具，为最终用户提供了一个更完整的海洋变化情况。除气候监测和研究外，海洋再分析还用于初始化亚季节到多年期的预测，支持观测网络监测，并评估气候模型模拟。这些应用需要可靠的不确定性估计和适合目的的评估，这可以通过数据同化和协调的相互比较活动的持续进展来实现。海洋再分析面临着具体的挑战：i）处理间歇性或中断的观测网络，ii）再现气候监测综合诊断的年际变率和趋势，iii）解释由于例如海气通量或海洋混合误差造成的漂移和偏差，iv）优化初始化并改善数据稀疏时期和区域的性能。其他挑战，如多尺度数据同化，以协调中尺度和大尺度的变化和流量依赖的误差特性的快速演变的过程中，放大长期再分析。在时间上向后扩展再分析的需求需要解决所有这些挑战，特别是在地球系统再分析和耦合数据同化的新兴背景下。这一小型审查旨在记录海洋再分析界的最新进展，讨论尚未解决的挑战，这些挑战需要持续开展活动，以最大限度地发挥海洋观测的效用，支持数据抢救，并推进再分析的具体研发要求。
Ocean reanalyses combine ocean models, atmospheric forcing fluxes, and observations using data assimilation to give a four-dimensional description of the ocean. Metrics assessing their reliability have improved over time, allowing reanalyses to become an important tool in climate services that provide a more complete picture of the changing ocean to end users. Besides climate monitoring and research, ocean reanalyses are used to initialize sub-seasonal to multi-annual predictions, to support observational network monitoring, and to evaluate climate model simulations. These applications demand robust uncertainty estimates and fit-for-purpose assessments, achievable through sustained advances in data assimilation and coordinated inter-comparison activities. Ocean reanalyses face specific challenges: i) dealing with intermittent or discontinued observing networks, ii) reproducing inter-annual variability and trends of integrated diagnostics for climate monitoring, iii) accounting for drift and bias due e.g. to air-sea flux or ocean mixing errors, iv) optimizing initialization and improving performances during periods and in regions with sparse data. Other challenges such as multi-scale data assimilation to reconcile mesoscale and large-scale variability and flow-dependent error characterization for rapidly evolving processes, are amplified in long-term reanalyses. The demand to extend reanalyses backward in time requires tackling all these challenges, especially in the emerging context of earth system reanalyses and coupled data assimilation. This mini-review aims at documenting recent advances from the ocean reanalysis community, discussing unsolved challenges that require sustained activities for maximizing the utility of ocean observations, supporting data rescue and advancing specific research and development requirements for reanalyses.