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

Atmospheric And Environmental Research Inc, Lexington MA

Investigators

Abstract

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.