2023
DOI: 10.1016/j.pocean.2022.102948
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A high-resolution ocean bottom temperature product for the northeast U.S. continental shelf marine ecosystem

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Cited by 9 publications
(2 citation statements)
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“…Bottom values (at depth) for temperature and oxygen were chosen because they represented the spatial habitat where fish were collected in bottom trawl surveys, and can also be a better predictor of species distributions from bottom trawl surveys when compared to sea surface temperature (i.e., [39]). Bottom temperature data were obtained from du Pontavice et al [40]. This long term, high-resolution bottom temperature time-series is derived from bias-corrected simulations of the Northwest Atlantic Ocean Regional Ocean Modelling System (ROMS-NWA; [41]) for the period 1972-1992 and from raw output from the Global Ocean Physics Reanalysis (Glorys12v1 reanalysis; [42]) for the period 1993-2019.…”
Section: Temperature and Oxygen Datamentioning
confidence: 99%
“…Bottom values (at depth) for temperature and oxygen were chosen because they represented the spatial habitat where fish were collected in bottom trawl surveys, and can also be a better predictor of species distributions from bottom trawl surveys when compared to sea surface temperature (i.e., [39]). Bottom temperature data were obtained from du Pontavice et al [40]. This long term, high-resolution bottom temperature time-series is derived from bias-corrected simulations of the Northwest Atlantic Ocean Regional Ocean Modelling System (ROMS-NWA; [41]) for the period 1972-1992 and from raw output from the Global Ocean Physics Reanalysis (Glorys12v1 reanalysis; [42]) for the period 1993-2019.…”
Section: Temperature and Oxygen Datamentioning
confidence: 99%
“…Regional ocean circulation changes can be more pronounced in specific seasons and can be discerned through temperature change. The NEFSC has developed a new ocean bottom temperature product at a very high temporal and spatial resolution (daily, 1/12˚) that combines three different ocean models, a bias corrected regional ocean model, a global ocean reanalysis, and an ocean forecast, resulting in a daily time series from 1959-present [61]. This high-resolution bottom temperature historical time series would not be possible using in situ observations alone and it can be used to fill in spatial and temporal gaps in survey data and understand seasonal, interannual, and decadal variability with much less uncertainty.…”
Section: Plos Climatementioning
confidence: 99%