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Arctic Tidal Constituent Atlas (ArcTiCA) : A database of tide elevation constituents for the Arctic region from 1800 through present day.

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DataCite Commons2024-01-19 更新2025-04-16 收录
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https://arcticdata.io/catalog/view/doi:10.18739/A2VT1GR64
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In the Arctic Ocean, tides affect ocean circulation and mixing, and sea ice dynamics and thermodynamics. Significant advances have been made in global ocean tide models; however, their performance in the Arctic is hampered by poorly-mapped bottom topography, the dynamical influence of sea ice on tides, and limitations on satellite altimetry measurements due to the high latitudes and presence of sea ice. An additional factor is the limited availability of sea surface height (SSH) data in the Arctic. In situ measurements from coastal tide gauges and ocean bottom pressure sensors are crucial sources of information that can be used to understand the spatial variability of tides, interpret satellite SSH records that are undersampled in time, and validate the advances made in tide models. Global in situ tidal constituent databases contain values for a limited number of sites in the Arctic; for example, TICON-3 (Hart-Davis et al 2022) contains 111 stations above 60°N and 21 above 70°N, with most of these being around North America and Norway. Here, we present a comprehensive dataset of tidal constituents in the Arctic region. This dataset combines analyses of in situ measurements from coastal tide gauges, ocean bottom pressure sensors and global navigation satellite system (GNSS) reflectometry, which results in tidal coefficients for 914 sites above 60°N and 399 above 70°N with a much greater spatial distribution across the full Arctic Ocean than for existing global tidal datasets. The resultant dataset is quality assessed and compared to recent tide models to determine the reliability of the different data sources used. Hart-Davis, M.G., Dettmering, D., & Seitz, F. (2022). TICON-3: Tidal Constants based on GESLA-3 sea-level records from globally distributed tide gauges including gauge type information (data). PANGAEA, https://doi.org/10.1594/PANGAEA.951610
提供机构:
NSF Arctic Data Center
创建时间:
2024-01-19
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