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| Collaborative Research: Development of a Carbon Seaglider for ocean acidification monitoring and inorganic carbon process studies | |
| 项目编号 | 1841948 |
| Claudine Hauri | |
| 项目主持机构 | University of Alaska Fairbanks Campus |
| 开始日期 | 2018-09-01 |
| 结束日期 | 08/31/2022 |
| 英文摘要 | The oceanic reservoir of carbon dioxide is large, dynamic, spatially variable, and of critical importance to Earth?s climate, biogeochemical cycles, and the health of marine ecosystems. At present, the partial pressure of carbon dioxide (pCO2) is vastly undersampled throughout the oceans. This is due to conventional sampling approaches that rely primarily on discrete water sample collections from dedicated research cruises, underway measurements of surface ocean properties from transiting vessels, or time series measurements from in situ sensors on fixed moorings. This sparse sampling coverage greatly limits the understanding of the spatial and temporal variability of carbon dioxide, the processes that control its cycling, and how its accumulation in the ocean impacts marine life via ocean acidification. The researchers will develop a Carbon Seaglider that will, for the first time, be capable of autonomously measuring pCO2 at high resolution throughout the water column. Once available to the community, the Carbon Seaglider will advance the understanding of regional and global carbon cycling, ocean productivity, ocean acidification, and the ocean?s role in mitigating climate change. The Carbon Seaglider could also be applied to remote monitoring of the chemical habitat of CO2-sensitive organisms and thereby refine the understanding of ecosystem responses to ocean acidification. Enhanced monitoring of subsurface waters is also important to advance the early warning system for shellfish hatcheries and fishermen. The researchers will develop an autonomous Carbon Seaglider by integrating a robust, proven and highly accurate pCO2 sensor (Kongsberg CONTROS HydroC CO2) into a highly capable, state-of-the-art autonomous coastal underwater glider (Kongsberg Seaglider C2). The primary products of this project will be a proven, science-ready pCO2-sensing Seaglider that is commercially available for a variety of ocean observing missions. This Carbon Seaglider will be accompanied by all of the software packages and operational documentation necessary to ensure user-friendly operation and high-quality data products. The new Carbon Seaglider will for the first time provide the ability to autonomously conduct high-resolution and adaptively sampled pCO2 measurements throughout the water column and across large range of spatial and temporal scales. Successful completion of this project will advance the Carbon Seaglider system to its final form and one that is proven to work effectively and reliably under a wide range of environmental conditions. This involves the final integration of these proven components into a fully functional system, optimization of its performance and operation, and rigorous developmental testing, evaluation, and operational demonstration during scientific mission. The proposed science mission in glacial meltwater affected Prince William Sound challenges both the pCO2 sensing capabilities (i.e. dynamics and variations) as well as the glider platform? capability (i.e. strong currents and density gradients). If these demonstration experiments are successful, it would prove that the Carbon Seaglider can be used for a variety of other scientific and monitoring missions, most of which would involve operations in much less demanding environments. 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 | $1,296,143.00 |
| 项目类型 | Continuing 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/211918 |
| 推荐引用方式 GB/T 7714 | Claudine Hauri.Collaborative Research: Development of a Carbon Seaglider for ocean acidification monitoring and inorganic carbon process studies.2018. |
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