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| SODA4: ocean climate variability at mesoscale resolution | |
| 项目编号 | 1948952 |
| James Carton | |
| 项目主持机构 | University of Maryland, College Park |
| 开始日期 | 2020-03-15 |
| 结束日期 | 02/28/2023 |
| 英文摘要 | Oceanographic observations are sparse and not uniformly distributed over space or time. Since many analyses benefit from complete fields available over a regular grid, reanalysis products have been developed to fill this gap by constraining a numerical model with available observations. One of the most widely used ocean reanalysis products is the Simple Ocean Data Assimilation. Its current version (SODA3) does not have sufficient resolution to capture most of the eddies, especially in the high latitude regions. This may cause biases in regions where strong eddy activity or wind forcing and mixing are present. This project exploits the growth of computational power to make improved use of the limited historical observational record using a model that resolves the dominant smaller scales of motion in order to produce a mesoscale resolving global ocean/sea ice reanalysis called SODA4. The project also includes a focused examination of the role of mesoscale processes in the Arctic and in subpolar/Arctic exchanges. This work is directed toward understanding the role the ocean and sea ice systems play in regulating and modifying Earth’s weather and climate partly as a guide to improve forecasts of future changes. Improved understanding of historical ocean variability benefits the scientific enterprise by playing a crucial role as a guide to improve forecasts of coupled climate variability and by adding additional value to the historical observational record by reconstructing their basin-scale context. By supporting development and distribution of more realistic historical climate reanalysis spanning the past four decades this project can serve to integrate research activities across multiple areas and disciplines. The improved representation of smaller scales of motion and of regions of high human impact such as the nearshore environment should also help inform a broad community (coastal planners and engineers, wind farms, the fisheries community, etc.) regarding historical ocean variability and change. This research project also serves educational mission of University of Maryland College Park in several ways. Most directly it will support the dissertation research of a graduate student at the Department of Atmospheric and Oceanic Science. It will also involve a number of undergraduate research projects. Examination of SODA3 results shows that its resolution is insufficient where mesoscale variability and near-surface diapycnic processes play dominant roles. This project explores the additional improvements to representation of the state of the ocean/sea ice system that can be gained by more completely representing oceanic mesoscale processes even during decades when mesoscale-resolving observing systems were not available. One region which will benefit from enhanced resolution is the Arctic Ocean and its connection to the subpolar gyres. The subpolar North Atlantic is the major route by which water is exchanged with the Arctic Ocean and this connection is of particular interest for many reasons. First, the surface water of the Nordic Seas is warming rapidly and the winter ice is retreating. Second, strong decadal temperature variability is present with unknown consequences for the central Arctic. Third it is a key region of deepwater formation. This project thus includes a focused effort to improve representation and diagnosis of the dynamics of subpolar/Arctic exchanges and their connection to variable Arctic Ocean water masses. 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. |
| 资助机构 | US-NSF |
| 项目经费 | $960,486.00 |
| 项目类型 | Standard Grant |
| 国家 | US |
| 语种 | 英语 |
| 文献类型 | 项目 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/212868 |
| 推荐引用方式 GB/T 7714 | James Carton.SODA4: ocean climate variability at mesoscale resolution.2020. |
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