GSTDTAP
项目编号1632090
RAPID: Offshore export of riverine water in the South Atlantic Bight during a strong El Nino event
Patricia Medeiros
主持机构University of Georgia Research Foundation Inc
项目开始年2016
2016-03-01
项目结束日期2018-02-28
资助机构US-NSF
项目类别Standard Grant
项目经费40296(USD)
国家美国
语种英语
英文摘要The Identification of transport pathways and offshore export of riverine water on continental shelves is important because the input of low salinity water influences shelf hydrography and dynamics, as well as its biogeochemical processes. Off-shelf export of riverine water, and the material it contains, into the Gulf Stream has the potential to spread their signatures over large areas of the North Atlantic, and to potentially sequester riverine-derived carbon away from the surface into subsurface water of the subtropical gyre. However, standard in situ sampling only allows for relatively low resolution observations over relatively small areas, making it difficult to investigate distribution and export of low-salinity water, since those can occur in narrow filaments that are easily missed by in situ sampling. The combination of the in situ data and drifter trajectories with the recently-developed algorithm to retrieve salinity in the region will allow for comparisons between normal years-the project has an extensive data set collected during seven research cruises, and an extreme year in terms of river discharge associated with one of the strongest El Nino events in the last 70+years. This project will promote education by supporting one graduate and one undergraduate student. Findings from this research project will also be disseminated in the LTER Schoolyard Program that is organized every summer by the NSF-funded Georgia Coastal Ecosystem Long-Term Ecological Research site in which science and math K-12 teachers from across the State of Georgia are immersed in hands-on research activities and discussions on coastal processes. Training K-12 teachers will maximize the dissemination of the knowledge to a large audience, since each teacher has the opportunity to interact with a large number of students from across the State. All data sets generated as part of this project will be made publicly available.

This project will examine the offshore export of riverine water in the shallow and broad continental shelf of the South Atlantic Bight (SAB) during the strong El Nino currently underway, which is on track to rival the strength of the 1997/1998 event. River discharge in the SAB is strongly influenced by El Ninos, with the highest discharge ever recorded at the Altamaha River having occurred during the strong 1997/98 event. Discharge in early 2016 is already two standard deviations above the long-term average for the same period, indicating that the SAB will likely receive very high river flow during spring 2016. This provides a once-in-many-decades opportunity to investigate transport pathways and the mechanisms controlling the offshore export of riverine water over the shelf under extreme conditions. The project's investigators will take advantage of a research cruise of opportunity in spring 2016 and use a combination of in situ data and a recently-developed algorithm to retrieve salinity from satellite observations. The data set will be complemented by multiple surface drifter deployments at the Altamaha River mouth and along a cross-shelf transect extending from the inner shelf to the slope. The distribution and export of riverine water over the shelf in 2016, under extreme conditions associated with El Nino, will be compared with the distribution and export in 2014, when discharge was near the historical average and an extensive data set was collected during seven research cruises in the region. The role played by eddies and winds on cross-shelf transport of riverine water will also be assessed and compared for the past two years.
来源学科分类Geosciences - Ocean Sciences
文献类型项目
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/69161
专题环境与发展全球科技态势
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Patricia Medeiros.RAPID: Offshore export of riverine water in the South Atlantic Bight during a strong El Nino event.2016.
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