The Gulf Stream, a major ocean current in the North Atlantic ocean is a key component in the global redistribution of heat and is important for marine ecosystems. Based on 27 years (1993–2019) of wind reanalysis and satellite altimetry measurements, we present observational evidence that the path of this freely meandering jet after its separation from the continental slope at Cape Hatteras, aligns with the region of maximum cyclonic vorticity of the wind stress field known as the positive vorticity pool. This synchronicity between the wind stress curl maximum region and the Gulf Stream path is observed at multiple time-scales ranging from months to decades, spanning a distance of 1500 km between 70 and 55W. The wind stress curl in the positive vorticity pool is estimated to drive persistent upward vertical velocities ranging from 5 to 17 cm day−1over its ~ 400,000 km2area; this upwelling may supply a steady source of deep nutrients to the Slope Sea region, and can explain as much as a quarter of estimated primary productivity there.
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Pan, J (Ed.)
Abstract Free, publicly-accessible full text available December 1, 2025 -
Porter, Nicholas ; Gangopadhyay, Avijit (Ed.)This dataset consists of weekly trajectory information of Gulf Stream Warm Core Rings (WCR) that existed between 2021 and 2023. This work builds upon two previous datasets: (i) Warm Core Ring trajectory information from 2000 to 2010 -- Porter et al. (2022) (https://doi.org/10.5281/zenodo.7406675) (ii) Warm Core Ring trajectory information from 2011 to 2020 -- Silver et al. (2022a) (https://doi.org/10.5281/zenodo.6436380). Combining these three datasets (previous two and this one), a total of 24 years of weekly Warm Core Ring trajectories are now available. An example of how to use such a dataset can be found in Silver et al. (2022b). The format of the dataset is similar to that of Porter et al. (2022) and Silver et al. (2022a), and the following description is adapted from those datasets. This dataset is comprised of individual files containing each ring’s weekly center location and its surface area for 81 WCRs that existed and tracked between January 1, 2021 and December 31, 2023 (5 WCRs formed in 2020 and still existed in 2021; 28 formed in 2021; 30 formed in 2022; 18 formed in 2023). Each Warm Core Ring is identified by a unique alphanumeric code 'WEyyyymmddX', where 'WE' represents a Warm Eddy (as identified in the analysis charts); 'yyyymmdd' is the year, month and day of formation; and the last character 'X' represents the sequential sighting (formation) of the eddy in that particular year. Continuity of a ring which passes from one year to the next is maintained by the same character in the previous year and absorbed by the initial alphabets for the next year. For example, the first ring formed in 2022 has a trailing alphabet of 'H', which signifies that a total of seven rings were carried over from 2021 which were still present on January 1, 2022 and were assigned the initial seven alphabets (A, B, C, D, E, F and G). Each ring has its own netCDF (.nc) filename following its alphanumeric code. Each file contains 4 variables every week, “Lon”- the ring center’s longitude, “Lat”- the ring center’s latitude, “Area” - the rings size in km^2, and “Date” in days – which is the number of days since Jan 01, 0000. Five rings formed in the year 2020 that carried over into the year 2021 were included in this dataset. These rings include ‘WE20200724Q’, ‘WE20200826R’, ‘WE20200911S’, ‘WE20200930T’, and ‘WE20201111W’. The two rings that formed in 2023, and were carried over into the following year were included with their full trajectories going into the year 2024. These rings include ‘WE20231006U’ and ‘WE20231211W’. The process of creating the WCR tracking dataset follows the same methodology of the previously generated WCR census (Gangopadhyay et al., 2019, 2020). The Jenifer Clark’s Gulf Stream Charts (Gangopadhyay et al., 2019) used to create this dataset are 2-3 times a week from 2021-2023. Thus, we used approximately 360+ Charts for the 3 years of analysis. All of these charts were reanalyzed between -75° and -55°W using QGIS 2.18.16 (2016) and geo-referenced on a WGS84 coordinate system (Decker, 1986).more » « less
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Abstract We present observational evidence of a significant increase in Salinity Maximum intrusions in the Northeast US Shelf waters in the years following 2000. This increase is subsequent to and influenced by a previously observed regime-shift in the annual formation rate for Gulf Stream Warm Core Rings, which are relatively more saline than the shelf waters. Specifically, mid-depth salinity maximum intrusions, a cross-shelf exchange process, has shown a quadrupling in frequency on the shelf after the year 2000. This increase in intrusion frequency can be linked to a similar increase in Warm Core Ring occupancy footprint along the offshore edge of the shelf-break which has greatly increased the abundance of warm salty water within the Slope Sea. The increased ring occupancy footprint along the shelf follows from the near doubling in annual Warm Core Ring formation rate from the Gulf Stream. The increased occurrence of intrusions is likely driven by a combination of a larger number of rings in the slope sea and the northward shift in the GS position which may lead to more interactions between rings and the shelf topography. These results have significant implications for interpreting temporal changes in the shelf ecosystem from the standpoint of both larval recruitment as well as habitability for various important commercial species.
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This dataset includes multiple fields: (i) files for monthly and annual fields for the max curl line and the zero curl line at 0.1 degree longitudinal resolutions; (ii) files for monthly and annual GS path obtained from Altimetry and originally processed by Andres (2016) at 0.1 degree longitudinal resolution. The maximum curl line (MCL) and the zero curl line (ZCL) calculations are briefly described here and are based on the original wind data (at 1.25 x 1.25 degree) provided by the Japanese reanalysis (JRA-55; Kobayashi et al., 2015) and available at https://zenodo.org/record/8200832 (Gifford et al. 2023). For details see Gifford, 2023.
The wind stress curl (WSC) fields used for the MCL and ZCL calculations extend from 80W to 45W and 30N to 45N at the 1.25 by 1.25-degree resolution. The MCL is defined as the maximum WSC values greater than zero within the domain per 1.25 degree longitude. As such, it is a function of longitude and is not a constant WSC value unlike the zero contour. High wind stress curl values that occurred near the coast were not included within this calculation. After MCL at the 1.25 resolution was obtained the line was smoothed with a gaussian smoothing and interpolated on to a 0.1 longitudinal resolution. The smoothed MCL lines at 0.1 degree resolution are provided in separate files for monthly and annual averages (2 files). Similarly, 2 other files (monthly and annual) are provided for the ZCL.
Like the MCL, the ZCL is a line derived from 1.25 degree longitude throughout the domain under the condition that it's the line of zero WSC. The ZCL is constant at 0 and does not vary spatially like the MCL. If there are more than one location of zero curl for a given longitude the first location south of the MCL is selected. Similar to the MCL, the ZCL was smoothed with a gaussian smoothing and interpolated on to a 0.1 longitudinal resolution.
The above files span the years from 1980 through 2019. So, the monthly files have 480 months starting January 1980, and the annual files have 40 years of data. The files are organized with each row being a new time step and each column being a different longitude. Therefore, the monthly MCL and ZCL files are each 480 x 351 for the 0.1 resolution data. Similarly, the annual files are 40 x 351 for the 0.1 degree resolution data.
Note that the monthly MCLs and ZCLs are obtained from the monthly wind-stress curl fields. The annual MCLs and ZCLs are obtained from the annual wind-stress curl fields.
Since the monthly curl fields preserves more atmospheric mesoscales than the annual curl fields, the 12-month average of the monthly MCLs and ZCLs will not match with the annual MCLs and ZCLs derived from the annual curl field. The annual MCLs and ZCLs provided here are obtained from the annual curl fields and representative metrics of the wind forcing on an annual time-scale.
Furthermore, the monthly Gulf Stream axis path (25 cm isoheight from Altimeter, reprocessed by Andres (2016) technique) from 1993 through 2019 have been made available here. A total of 324 monthly paths of the Gulf Stream are tabulated. In addition, the annual GS paths for these 27 years (1993-2019) of altimetry era have been put together for ease of use. The monthly Gulf Stream paths have been resampled and reprocessed for uniqueness at every 0.1 degree longitude from 75W to 50W and smoothed with a 100 km (10 point) running average via matlab. The uniqueness has been achieved by using Consolidator algorithm (D’Errico, 2023).
Each monthly or annual GS path has 251 points between 75W to 50W at 0.1 degree resolution.
Please contact igifford@earth.miami.edu for any queries. {"references": ["Andres, M., 2016. On the recent destabilization of the Gulf Stream path downstream of Cape Hatteras. Geophysical Research Letters, 43(18), 9836-9842.", "D'Errico, J., 2023. Consolidator (https://www.mathworks.com/matlabcentral/fileexchange/ 8354-consolidator), MATLAB Central File Exchange. Retrieved June 17, 2023.", "Gifford, Ian. H., 2023. The Synchronicity of the Gulf Stream Free Jet and the Wind Induced Cyclonic Vorticity Pool. MS Thesis, University of Massachusetts Dartmouth. 75pp.", "Gifford, Ian, H., Avijit Gangopadhyay, Magdalena Andres, Glen Gawarkiewicz, Hilde Oliver, Adrienne Silver, 2023. Wind Stress, Wind Stress Curl, and Upwelling Velocities in the Northwest Atlantic (80-45W, 30-45N) during 1980-2019, https://zenodo.org/record/8200832.", "Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K., Kamahori, H., Kobayashi, C., Endo, H. and Miyaoka, K., 2015. The JRA-55 reanalysis: General specifications and basic characteristics.\u202fJournal of the Meteorological Society of Japan. Ser. II,\u202f93(1), pp.5-48. Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K., Kamahori, H., Kobayashi, C., Endo, H. and Miyaoka, K., 2015. The JRA-55 reanalysis: General specifications and basic characteristics.\u202fJournal of the Meteorological Society of Japan. Ser. II,\u202f93(1), pp.5-48."]} -
This dataset contains three netcdf files that pertain to monthly, seasonal, and annual fields of surface wind stress, wind stress curl, and curl-derived upwelling velocities over the Northwest Atlantic (80-45W, 30-45N) covering a forty year period from 1980 to 2019. Six-hourly surface (10 m) wind speed components from the Japanese 55-year reanalysis (JRA-55; Kobayashi et al., 2015) were processed from 1980 to 2019 over a larger North Atlantic domain of 100W to 10E and 10N to 80N. Wind stress was computed using a modified step-wise formulation, originally based on (Gill, 1982) and a non-linear drag coefficient (Large and Pond, 1981), and later modified for low speeds (Trenberth et al., 1989). See Gifford (2023) for more details.
After the six-hourly zonal and meridional wind stresses were calculated, the zonal change in meridional stress (curlx) and the negative meridional change in zonal stress (curly) were found using NumPy’s gradient function in Python (Harris et al., 2020) over the larger North Atlantic domain (100W-10E, 10-80N). The curl (curlx + curly) over the study domain (80-45W, 10-80N) is then extracted, which maintain a constant order of computational accuracy in the interior and along the boundaries for the smaller domain in a centered-difference gradient calculation.
The monthly averages of the 6-hour daily stresses and curls were then computed using the command line suite climate data operators (CDO, Schulzweida, 2022) monmean function. The seasonal (3-month average) and annual averages (12-month average) were calculated in Python using the monthly fields with NumPy (NumPy, Harris et al., 2020).
Corresponding upwelling velocities at different time-scales were obtained from the respective curl fields and zonal wind stress by using the Ekman pumping equation of the study by Risien and Chelton (2008; page 2393). Please see Gifford (2023) for more details.
The files each contain nine variables that include longitude, latitude, time, zonal wind stress, meridional wind stress, zonal change in meridional wind stress (curlx), the negative meridional change in zonal wind stress (curly), total curl, and upwelling. Units of time begin in 1980 and are months, seasons (JFM etc.), and years to 2019. The longitude variable extends from 80W to 45W and latitude is 30N to 45N with uniform 1.25 degree resolution.
Units of stress are in Pascals, units of curl are in Pascals per meter, and upwelling velocity is described by centimeters per day. The spatial grid is a 29 x 13 longitude x latitude array.
Filenames:
monthly_windstress_wsc_upwelling.nc: 480 time steps from 80W to 45W and 30N to 45N.
seasonal_windstress_wsc_upwelling.nc: 160 time steps from 80W to 45W and 30N to 45N.
annual_windstress_wsc_upwelling.nc: 40 time steps from 80W to 45W and 30N to 45N.
Please contact igifford@earth.miami.edu for any queries. {"references": ["Gifford, I.H., 2023. The Synchronicity of the Gulf Stream Free Jet and the Wind Induced Cyclonic Vorticity Pool. MS Thesis, University of Massachusetts Dartmouth. 75pp.", "Gill, A. E. (1982). Atmosphere-ocean dynamics (Vol. 30). Academic Press.", "Harris, C.R., Millman, K.J., van der Walt, S.J. et al. Array programming with NumPy. Nature 585, 357\u2013362 (2020). DOI: 10.1038/s41586-020-2649-2.", "Japan Meteorological Agency/Japan (2013), JRA-55: Japanese 55-year Reanalysis, Daily 3-Hourly and 6-Hourly Data, https://doi.org/10.5065/D6HH6H41, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, Boulder, Colo. (Updated monthly.)", "Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K., Kamahori, H., Kobayashi, C., Endo, H. and Miyaoka, K., 2015. The JRA-55 reanalysis: General specifications and basic characteristics.\u202fJournal of the Meteorological Society of Japan. Ser. II,\u202f93(1), pp.5-48.", "Large, W.G. and Pond, S., 1981. Open ocean momentum flux measurements in moderate to strong winds.\u202fJournal of physical oceanography,\u202f11(3), pp.324-336.", "Risien, C.M. and Chelton, D.B., 2008. A global climatology of surface wind and wind stress fields from eight years of QuikSCAT scatterometer data.\u202fJournal of Physical Oceanography,\u202f38(11), pp.2379-2413.", "Schulzweida, Uwe. (2022). CDO User Guide (2.1.0). Zenodo. https://doi.org/10.5281/zenodo.7112925.", "Trenberth, K.E., Large, W.G. and Olson, J.G., 1989. The effective drag coefficient for evaluating wind stress over the oceans.\u202fJournal of Climate,\u202f2(12), pp.1507-1516."]} -
This dataset consists of weekly trajectory information of Gulf Stream Warm Core Rings from 2000-2010. This work builds upon Silver et al. (2022a) ( https://doi.org/10.5281/zenodo.6436380) which contained Warm Core Ring trajectory information from 2011 to 2020. Combining the two datasets a total of 21 years of weekly Warm Core Ring trajectories can be obtained. An example of how to use such a dataset can be found in Silver et al. (2022b).
The format of the dataset is similar to that of Silver et al. (2022a), and the following description is adapted from their dataset. This dataset is comprised of individual files containing each ring’s weekly center location and its area for 374 WCRs present between January 1, 2000 and December 31, 2010. Each Warm Core Ring is identified by a unique alphanumeric code 'WEyyyymmddA', where 'WE' represents a Warm Eddy (as identified in the analysis charts); 'yyyymmdd' is the year, month and day of formation; and the last character 'A' represents the sequential sighting of the eddies in a particular year. Continuity of a ring which passes from one year to the next is maintained by the same character in the first sighting. For example, the first ring in 2002 having a trailing alphabet of 'F' indicates that five rings were carried over from 2001 which were still observed on January 1, 2002. Each ring has its own netCDF (.nc) filename following its alphanumeric code. Each file contains 4 variables, “Lon”- the ring center’s weekly longitude, “Lat”- the ring center’s weekly latitude, “Area” - the rings weekly size in km2, and “Date” in days - representing the days since Jan 01, 0000.
The process of creating the WCR tracking dataset follows the same methodology of the previously generated WCR census (Gangopadhyay et al., 2019, 2020). The Jenifer Clark’s Gulf Stream Charts used to create this dataset are 2-3 times a week from 2000-2010. Thus, we used approximately 1560 Charts for the 10 years of analysis. All of these charts were reanalyzed between 75° and 55°W using QGIS 2.18.16 (2016) and geo-referenced on a WGS84 coordinate system (Decker, 1986).
Silver, A., Gangopadhyay, A, & Gawarkiewicz, G. (2022a). Warm Core Ring Trajectories in the Northwest Atlantic Slope Sea (2011-2020) (1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6436380
Silver, A., Gangopadhyay, A., Gawarkiewicz, G., Andres, M., Flierl, G., & Clark, J. (2022b). Spatial Variability of Movement, Structure, and Formation of Warm Core Rings in the Northwest Atlantic Slope Sea. Journal of Geophysical Research: Oceans, 127(8), e2022JC018737. https://doi.org/10.1029/2022JC018737
Gangopadhyay, A., G. Gawarkiewicz, N. Etige, M. Monim and J. Clark, 2019. An Observed Regime Shift in the Formation of Warm Core Rings from the Gulf Stream, Nature - Scientific Reports, https://doi.org/10.1038/s41598-019-48661-9. www.nature.com/articles/s41598-019-48661-9.
Gangopadhyay, A., N. Etige, G. Gawarkiewicz, A. M. Silver, M. Monim and J. Clark, 2020. A Census of the Warm Core Rings of the Gulf Stream (1980-2017). Journal of Geophysical Research, Oceans, 125, e2019JC016033. https://doi.org/10.1029/2019JC016033.
QGIS Development Team. QGIS Geographic Information System (2016).
Decker, B. L. World Geodetic System 1984. World geodetic system 1984 (1986).
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null (Ed.)Abstract As the Gulf Stream separates from the coast, it sheds both Warm and Cold Core Rings between $$75^\circ$$ 75 ∘ and $$55^\circ \,\hbox {W}$$ 55 ∘ W . We present evidence that this ring formation behavior has been asymmetric over both interannual and seasonal time-scales. After a previously reported regime-shift in 2000, 15 more Warm Core Rings have been forming yearly compared to 1980–1999. In contrast, there have been no changes in the annual formation rate of the Cold Core Rings. This increase in Warm Core Ring production leads to an excess heat transfer of 0.10 PW to the Slope Sea, amounting to 7.7–12.4% of the total Gulf Stream heat transport, or 5.4–7.3% of the global oceanic heat budget at $$30^\circ \,\hbox {N}$$ 30 ∘ N . Seasonally, more Cold Core Rings are produced in the winter and spring and more Warm Core Rings are produced in the summer and fall leading to more summertime heat transfer to the north of the Stream. The seasonal cycle of relative ring formation numbers is strongly correlated (r = 0.82) with that of the difference in upper layer temperatures between the Sargasso and Slope seas. This quantification motivates future efforts to understand the recent increasing influence of the Gulf Stream on the circulation and ecosystem in the western North Atlantic.more » « less
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Abstract Gulf Stream Warm Core Rings (WCRs) have important influences on the New England Shelf and marine ecosystems. A 10‐year (2011–2020) WCR dataset that tracks weekly WCR locations and surface areas is used here to identify the rings' path and characterize their movement between 55 and 75°W. The WCR dataset reveals a very narrow band between 66 and 71°W along which rings travel almost due west along ∼39°N across isobaths – the “Ring Corridor.” Then, west of the corridor, the mean path turns southwestward, paralleling the shelfbreak. The average ring translation speed along the mean path is 5.9 cm s−1. Long‐lived rings (lifespan >150 days) tend to occupy the region west of the New England Seamount Chain (NESC) whereas short‐lived rings (lifespan <150 days) tend to be more broadly distributed. WCR vertical structures, analyzed using available Argo float profiles indicate that rings that are formed to the west of the NESC have shallower thermoclines than those formed to the east. This tendency may be due to different WCR formation processes that are observed to occur along different sections of the Gulf Stream. WCRs formed to the east of the NESC tend to form from a pinch‐off mechanism incorporating cores of Sargasso Sea water and a perimeter of Gulf Stream water. WCRs that form to the west of the NESC, form from a process called an aneurysm. WCRs formed through aneurysms comprise water mostly from the northern half of the Gulf Stream and are smaller than the classic pinch‐off rings.
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Abstract Fluctuations in the path of the Gulf Stream (GS) have been previously studied by primarily connecting to either the wind‐driven subtropical gyre circulation or buoyancy forcing via the subpolar gyre. Here we present a statistical model for 1 year predictions of the GS path (represented by the GS northern wall—GSNW) between
W and W incorporating both mechanisms in a combined framework. An existing model with multiple parameters including the previous year's GSNW index, center location, and amplitude of the Icelandic Low and the Southern Oscillation Index was augmented with basin‐wide Ekman drift over the Azores High. The addition of the wind is supported by a validation of the simpler two‐layer Parsons‐Veronis model of GS separation over the last 40 years. A multivariate analysis was carried out to compare 1‐year‐in‐advance forecast correlations from four different models. The optimal predictors of the best performing model include: (a) the GSNW index from the previous year, (b) gyre‐scale integrated Ekman Drift over the past 2 years, and (c) longitude of the Icelandic Low center lagged by 3 years. The forecast correlation over the 27 years (1994–2020) is 0.65, an improvement from the previous multi‐parameter model's forecast correlation of 0.52. The improvement is attributed to the addition of the wind‐drift component. The sensitivity of forecasting the GS path after extreme atmospheric years is quantified. Results indicate the possibility of better understanding and enhanced predictability of the dominant wind‐driven variability of the Atlantic Meridional Overturning Circulation and of fisheries management models that use the GS path as a metric.