Collaborative Research: A global assessment of annual to decadal sea level predictability

这项研究将确定我们目前在从年到年代际的时间尺度和跨越全球的空间尺度上预测海平面变化的能力的稳健性。这项研究将使用一个考虑海洋和大气过程的群落模型来模拟海平面的变化。模型结果将与现有数据进行比较，确定模拟和预测的技巧，同时阐明模型数据差异的原因。最终，该研究将提出是否可以用海洋和大气过程来描述海平面的变化，以及是否可以实现海平面变化的可预测性。海平面变率和可预测性的适当表示对全世界沿海社区具有根本意义。首席研究员正在与政府和私人实体就海平面可预测性进行合作。该项目将量化模式在全球范围内模拟和预测年至十年海平面变化的能力。社区地球系统模型（CESM）的技能将在水平分辨率为1度和0.1度的情况下确定，同时将模型结果与验潮仪数据、测高测量和大气压力再分析相结合。通过对远强迫和局地强迫的划分，以及通过海平面异常在整个海洋的传播，可以获得对海平面变率的机制理解。海平面异常将被分解为各种组件：静态与动态，外部强迫和非强迫，压力测量与空间，本地与远程强迫。模式模拟的相互比较将确定模式误差和随机变率对整个地球预测能力的影响。机制分析将提高预测的可靠性；推荐观察实验和模型实验；并提出海洋和气候变率表征的局限性。就更广泛的影响而言，该项目将对经济、文化和生态资源产生影响。该项目将代表与NCAR的合作，促进模型（CESM）的实施。由于海平面变化的预测对沿海规划至关重要，本项目将有助于评估CESM在年至年代际尺度上的误差，并将其与热量、动量和淡水通量、平流和波浪传播联系起来。PI正在与地方和州政府以及私营部门进行可预测性工作。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This study will determine the robustness of our current ability to predict sea-level variability at temporal scales from annual to decadal and at spatial scales that span the globe. The study will use a community model that considers processes in the ocean and in the atmosphere to simulate sea-level variability. The model results will be compared to data that are already available and determine the skill of the simulations and predictions, while elucidating the causes for model-data disparities. Ultimately, the study will propose whether sea-level variability can be described, and its predictability can be achieved, with oceanic and atmospheric processes. Appropriate representation of sea-level variability and predictability has fundamental implications for coastal communities worldwide. The principal investigator has ongoing efforts with government and private entities related to sea-level predictability.This project will quantify the ability of models to simulate and predict annual to decadal sea-level variability at a global scale. The skill of the Community Earth System Model (CESM) will be determined with horizontal resolutions of 1 and 0.1 degrees, while combining model results with tide gauge data, altimetry measurements and atmospheric pressure reanalysis. A mechanistic understanding of sea-level variability will be achieved by partitioning of remote and local forcing, as well as via the propagation of sea-level anomalies throughout the ocean. Sea-level anomalies will be deconstructed into various components: static vs dynamic, externally forced and unforced, manometric vs steric, local vs remote forcing. Intercomparisons of model simulations will identify the effects of model errors and random variability on the predictive skill throughout Earth. The mechanistic analyses will increase reliability of predictions; recommend observational and model experiments; and suggest limitations of ocean and climate variability representations. In terms of broader impacts, the project will have impacts on economic, cultural and ecological resources. The project will represent a collaboration with NCAR, facilitating the model (CESM) implementation. As predictions of sea-level variability are essential for coastal planning, this project will contribute to assess errors of CESM at scales of annual to decadal and relate them to heat, momentum and freshwater fluxes, advection and wave propagation. The PI has ongoing predictability efforts with local and state governments, as well as with the private sector.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.