Collaborative Research: Exploring centennial changes in ocean circulation with SODA

该项目扩展了正在进行的努力（SODA：简单海洋数据同化），以探索潜力以及建模和数据同化的局限性，旨在使用并行海洋计划（POP）重建海洋环流的百年分析。该领域是全球海洋，重点是海洋上层，那里的观测记录更丰富。主要时间段是上个世纪的后半期（1950-2007年），如果能够确定世纪的前半期有足够的观测数据来提供对海洋状况的可靠估计，则着眼于将其扩展到上个世纪。第一项工作是收集再分析所需的观测和地面强迫数据集。事实上，该项目的动机是气象学家做出相应的努力，以产生百年大气再分析。将对进入同化的信息的误差统计进行彻底的调查。第二个努力是探索一个更复杂的同化计划的基础上，本地包络变换卡尔曼滤波器的变化。这一变化将允许数据同化的属性，如温度-盐度误差协方差，在整个再分析期间演变，而不是被固定的先验。注意力也将集中在改进混合层结构的表示上。再分析实验的结果将用于探索各种海洋气候信号的结构和演变，如厄尔尼诺？太平洋的南方涛动（ENSO）和全球海洋的十年变化。总体目标是探索海洋数据同化可用于产生海洋参考气候的程度，而海洋参考气候又可作为审查其他物理、化学和生物分析产品的基础，为观测集提供大尺度背景，以及为海洋研究提供背景。知识价值：这项研究将导致对海洋物理状态的百年再分析的潜力的理解，重点是1000米以上。将制作百年再分析，并将其与强迫和海洋数据集一起沿着提供给社区。知识价值在于这种重新分析的潜力，以开辟新的问题，关于海洋？气候变化的作用。其结果将用于对季节、年际和十年时间尺度的变率进行诊断性检查，包括检查大气气候变率的协变。最后，将把海洋再分析产品与独立的观测集进行比较，以便了解再分析中的不确定性，更广泛的影响：SODA再分析目前正被世界各地的研究人员使用，由于覆盖期较长和采用了新的同化方案，应该对这些新的再分析产生相当大的兴趣。这项工作产生的一系列再分析实验将提供给社区，并将为学生和研究人员探索海洋气候变异性提供许多机会。除了对马里兰州大学和得克萨斯A M大学的研究生进行海洋数据同化培训外，再分析还可用作其他机构研究生的基础和课堂教学的资源。

This project extends an on-going effort (SODA: Simple Ocean Data Assimilation) to explore the potential as well as the limitations of modeling and data assimilation directed toward reconstruction of a centennial analysis of ocean circulation using the Parallel Ocean program (POP). The domain is the global ocean, with an emphasis on the upper ocean where the observational record is more substantial. The main time period is the second half of the last century (1950-2007) with an eye to expand it to the last century if it can established that there are enough observations in the first half of the century to provide reliable estimate of the state of the ocean.. The first effort is to assemble the observations and surface forcing data sets needed for this reanalysis. Indeed, the project is motivated by a corresponding effort by meteorologists to produce a centennial atmospheric reanalysis. A thorough investigation of the error statistics of information that goes into the assimilation will be conducted. The second effort is to explore a change to a more sophisticated assimilation scheme based on the Local Ensemble Transform Kalman Filter. This change would allow properties of the data assimilation such as temperature-salinity error covariances to evolve throughout the reanalysis period, rather than being fixed a priori. Attention will also be focused on improving representation of the structure of the mixed layer. The results of the reanalysis experiments will then be used to explore the structure and evolution of a variety of ocean climate signals such as the El Nino?Southern Oscillation (ENSO) in the Pacific Ocean and decadal variability in the global oceans. The overall goal is to explore the extent to which ocean data assimilation may be used to produce a reference climate for the oceans that in turn can serve as the basis for examining other physical, chemical, and biological analysis products, for providing the large-scale context for observation sets, as well as for studies of the ocean?s contribution to climate variability.Intellectual merit: This research will result in understanding of the potential of a centennial reanalysis of the physical state of the ocean with emphasis on the upper 1000m. Centennial reanalyses will be produced and made available to the community, along with the forcing and ocean data sets. The intellectual merit lies in the potential of this kind of reanalysis to open up new questions regarding the ocean?s role in climate variability. The results will be used to carry out diagnostic examination of variability on seasonal, interannual, and decadal timescales including examination of covariations of atmospheric climate variability. Finally, the ocean reanalysis product will be compared to independent observation sets in order to learn about the uncertainties in the reanalysis.Broader impacts: SODA reanalyses are currently being used by researchers from around the world and there should be considerable interest in these new reanalyses, both because of the longer period of coverage and because of the new assimilation scheme. The set of reanalysis experiments resulting from this work will be made available to the community and will offer many opportunities for students and researchers to explore ocean climate variability. In addition to training graduate students at the University of Maryland and at Texas A&M University in ocean data assimilation, the reanalysis can be used as the foundation for graduate students at other institutions and as a resource for classroom teaching.