Observing and modeling the spatiotemporal variability of the seasonal cycle in sea level

观测和模拟海平面季节周期的时空变化

• 批准号: 2239805
• 负责人: Rui Ponte
• 金额: $ 56.33万
• 依托单位: Atmospheric and Environmental Research Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2239805&HistoricalAwards=false
• 关键词: Observing; modeling; spatiotemporal; variability; seasonal

Monthly sea-level variability over extensive areas of the global oceans, including coastal regions, is dominated by a seasonal cycle. Seasonal variations of sea level can be equivalent to sea-level rise that occurs over decades and can pre-dispose coastal regions to increased flooding from storm surge and tides. This project leverages recent developments in observations and computer models to address the following questions: How does the seasonal cycle in coastal sea level relate to that over the deep ocean? What physical mechanisms determine that relationship? How consistent are model and data representations of such seasonal variability? What factors can affect those representations? The specific objectives are to: (1) analyze the sea-level seasonal cycle, its mean and year-to-year variability, and its spatial structure over the global ocean including its coastal zones, based on data and models; (2) understand the causes of the spatial and temporal variability in the seasonal cycle of sea level; (3) assess model-based estimates of the sea-level seasonal cycle against data and understand their differences in terms of possible model and data shortcomings. Satellite and in situ measurements of sea level, ocean bottom pressure, plus water temperature and salinity will be combined to determine the seasonal cycle in sea level and the relative contributions from changes in water density. Close scrutiny will be given to the spatial structure of seasonal sea level, the connections between deep and shallow coastal regions, and to the year-to-year variations related to climate variability. Observational results will be compared to available model-based estimates, and thus assess the ability of the latter to explain the observed spatial and temporal characteristics of the seasonal cycle in sea level. Discrepancies will be used to examine needed improvements in modeling and observing systems. Detailed examination will determine the effects of atmospherically forced versus ocean internal variability associated with eddies. The planned data and model analyses will lead to developing better tools for sea-level forecasts and projections, allowing for better preparation of coastal communities for flood risks.This project seeks to study the seasonal variability in sea level over the global ocean and coastal regions. Specific objectives would be to a) analyze the seasonal cycle, its mean and year-to-year variability, as well as its spatial structure; b) diagnose the forcing and dynamics of the spatiotemporal variability in the sea-level seasonal cycle; and c) determine how well models and data assimilation systems represent these seasonal cycles and explore the causes for differences with the observations. These objectives would be addressed with altimetry, tide gauge, satellite gravity and in-situ temperature-salinity data, as well as with various model-based estimates from ECCO, GLORYS and OCCIPUT efforts. Analyses would allow separation of steric and manometric effects on the seasonal cycle. Emphasis would be placed in understanding differences between deep and shallow coastal areas and year-to-year variability related to climate. Efforts would also concentrate on determining the relative effects on the seasonal cycle of external atmospheric forcing vs intrinsic ocean variability associated with eddies and nonlinear processes. As broader impacts, detailed comparisons of data, models, and assimilation systems to be pursued under the project would lead to more informed requirements for data collection and model improvements and contribute towards developing better tools for SL forecasts and projections, allowing for better preparation of coastal communities for flood risks. This is aligned with major efforts of the World Climate Research Program in the theme of Regional Sea Level Change and Coastal Impacts. The collaborative proposal would involve researchers from France (Penduff, to analyze OCCIPUT) and Germany (Schindelegger, to analyze tide gauges and coastal altimetry data sets).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.

全球海洋广大地区，包括沿海地区，每月海平面的变化主要是季节性的。海平面的季节性变化相当于几十年来的海平面上升，使沿海地区更容易遭受风暴潮和潮汐造成的洪水。该项目利用观测和计算机模型的最新发展来解决以下问题：沿海海平面的季节性周期与深海海平面的季节性周期有何关系？是什么物理机制决定了这种关系？这种季节性变化的模型和数据表示有多一致？哪些因素会影响这些表现？具体目标是：（1）根据数据和模式分析海平面季节周期、其平均和逐年变化及其在全球海洋包括其沿海地区的空间结构;（2）了解海平面季节周期时空变化的原因;（3）对照数据评估基于模型的海平面季节性周期估计，并了解它们在可能的模型和数据缺陷方面的差异。将结合卫星和现场对海平面、洋底压力以及水温和盐度的测量，以确定海平面的季节性周期以及水密度变化的相对影响。将仔细研究季节性海平面的空间结构、深水和浅水沿海区域之间的联系以及与气候变异有关的逐年变化。观测结果将与现有的基于模型的估计数进行比较，从而评估后者解释观测到的海平面季节性周期的空间和时间特征的能力。离散性将用于检查建模和观测系统中需要的改进。详细的检查将确定与涡旋相关的大气强迫与海洋内部变化的影响。计划中的数据和模型分析将有助于开发更好的海平面预报和预测工具，使沿海社区更好地为洪水风险做好准备，该项目旨在研究全球海洋和沿海地区海平面的季节性变化。具体目标是：a）分析季节周期、其平均和逐年变化以及其空间结构; B）诊断海平面季节周期中时空变化的强迫和动态;和c）确定模型和数据同化系统代表这些季节周期的效果如何，并探索与观测差异的原因。这些目标将通过测高、验潮、卫星重力和现场温度-盐度数据，以及欧洲委员会通信组织、全球光遥感系统和奥赛普塔的各种基于模型的估计来实现。分析将允许分离空间和压力对季节循环的影响。重点将放在了解深水和浅水沿海地区之间的差异以及与气候有关的逐年变化。还将集中精力确定外部大气强迫与与涡旋和非线性过程相关的海洋固有变率对季节性周期的相对影响。作为更广泛的影响，在项目下对数据、模型和同化系统进行的详细比较将导致对数据收集和模型改进提出更知情的要求，并有助于开发更好的SL预测和预测工具，使沿海社区更好地为洪水风险做好准备。这与世界气候研究计划在区域海平面变化和沿海影响主题方面的主要努力是一致的。这项合作提案将涉及来自法国（Penduff，分析OCCIPUT）和德国（Schindelegger，分析潮汐测量和海岸测高数据集）的研究人员。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。