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

合作研究：对每年至十年海平面可预测性的全球评估

• 批准号: 2148596
• 负责人: Stephen Yeager
• 金额: $ 19.18万
• 依托单位: University Corporation For Atmospheric Res
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-15 至 2025-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2148596&HistoricalAwards=false
• 关键词: Collaborative; Research; global; assessment; annual

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.

这项研究将确定我们目前在从年度到十年的时间尺度和跨越地球仪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到海洋和大气过程的群落模型来模拟海平面变化。模型结果将与现有数据进行比较，并确定模拟和预测的技能，同时阐明模型数据差异的原因。最后，这项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，以及是否可以实现其可预测性。海平面变化和可预测性的适当表述对全世界沿海社区具有根本性的影响。首席研究员正在与政府和私营实体合作研究海平面的可预测性，该项目将量化模型在全球范围内模拟和预测年至十年海平面变化的能力。共同体地球系统模型的技术水平将根据1度和0.1度的水平分辨率来确定，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。通过对远程和本地强迫的划分以及通过海平面异常在整个海洋中的传播，将实现对海平面变化的机械理解。海平面异常将被分解成各种组成部分：静态与动态，外部强迫和非强迫，压力与空间，本地与远程强迫。模型模拟的相互比较将确定模型误差和随机变化对整个地球的预测技能的影响。机械分析将增加预测的可靠性;建议观测和模型实验;并提出海洋和气候变异性表示的局限性。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。由于海平面变化预测对沿海规划至关重要，该项目将有助于评估CESM在年度至十年尺度上的误差，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与地方和州政府以及私营部门持续开展可预测性工作。该奖项反映了NSF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。