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Year 1 of CPIES site C1 deployment. PDS data, via Iridium, returned on 9/1/2024 

Year 1 of CPIES site C2 deployment. PDS data, via Iridium, returned on 9/1/2024. 

{"Abstract":["Gulf Stream paths (daily, monthly, and annual) from 1993-01-01 to 2023-12-31 are identified via the longest 25-cm sea surface height contour in the Northwest Atlantic (75°W–55°W; 33°N–43°N) from the daily 1/8° resolution maps of absolute dynamic topography from the E.U. Copernicus Marine Service product Global Ocean Gridded Level 4 Sea Surface Heights and Derived Variables Reprocessed 1993 Ongoing, following the methodology of Andres (2016). The daily sea surface height fields are averaged to monthly and annual fields to identify the corresponding monthly and annual Gulf Stream paths. Additionally, an updated Gulf Stream destabilization point time series (1993–2023), which builds upon the work of Andres (2016), was generated using the E.U. Copernicus Marine Service product Global Ocean Gridded Level 4 Sea Surface Heights and Derived Variables Reprocessed 1993 Ongoing (1/8°). Similar to Andres (2016), the monthly Gulf Stream path is identified as the 25-cm SSH contour from absolute dynamic topography maps. The 12 monthly mean paths are divided yearly into 0.5° longitude bins (from 75°W to 55°W). In some months, the Gulf Stream can take a meandering path and contort over itself in an “S” curve. In these cases, the northernmost latitude is used in the variance calculation to resolve the issue of multiple latitudes for a single longitude. The variance of the Gulf Stream position (latitude) is then calculated for each year using the 12 monthly mean paths. The destabilization point is defined as the first downstream distance (longitude) at which the variance of the Gulf Stream position exceeds 0.4(°)2, which differs from the original threshold value of 0.5(°)2 in Andres (2016). The threshold value of 0.4(°)2 is the 70th percentile of variance for all years, which marks the transition from a relatively stable jet to an unstable, meandering current in the new higher-resolution (1/8°) maps of absolute dynamic topography.\n\nThanks to improvements in processing and combining satellite altimeter data (Taburet et al., 2019), in recent years the maps of absolute dynamic topography are different than the maps used by Andres (2016), which had 1/4° resolution. To account for the differences in the resolution of the data and corrections to the processing standards of altimeter data, a new threshold value was chosen that is consistent with the methods of Andres (2016), i.e., the threshold still signifies the transition between a stable and unstable Gulf Stream. However, a lower threshold value is necessary in the new absolute dynamic topography maps since finer-resolution data can separate distinct local maxima in variance, which could be smoothed together in coarser data, and may cause the destabilization point to be identified further downstream if the threshold were not adjusted. The 70th percentile of variance (0.4(°)2) for all years (1993–2023) was chosen as the threshold because the distribution of variance is right-skewed with a long tail and the 70th percentile separate lower variance associated with meridional shifts in the Gulf Stream path from the extreme, vigorous meadnering that occurs downstream of the "destabilization point".\n\nThe daily, monthly, annual Gulf Stream paths, and the updated destabilization point time series were generated using the E.U. Copernicus Marine Service product Global Ocean Gridded Level 4 Sea Surface Heights and Derived Variables Reprocessed 1993 Ongoing (https://doi.org/10.48670/moi-00148). \n\n \n\n "]} 

Abstract 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. 

Sustained observation is key to measuring physical and ecological variability in the Northwest Atlantic. Here we illustrate how a partnership with a merchant marine container vessel in service between New Jersey and Bermuda twice per week gives scientists a unique window into upper ocean currents, water properties, and marine ecology. Scientific observations collected from CMV Oleander, operated by Bermuda Container Line/Neptune Group, enable cross-disciplinary research, complement satellite measurements, and contribute to global observing programs—including the Global eXpendable BathyThermograph (XBT) Network, the Surface Ocean CO2 Atlas (SOCAT), and the Continuous Plankton Recorder (CPR) Survey. Recent co-located measurements along the Oleander Line document that fronts in temperature, salinity, and carbon dioxide concentrations align with the (sub)mesoscale circulation patterns. The sustained observations show warming and shrinking of the Slope Sea, a northward shift of the Gulf Stream, and warming of the “18°C water” (subtropical North Atlantic mode water) to 19°C. 

Abstract The Oleander project, a program to monitor upper ocean currents between Bermuda and New Jersey, started in fall 1992, at about the same time modern satellite altimetry began. This study has two purposes. First, it revisits earlier work that compared Oleander estimates of sea level with altimetry. They agree well with respect to mean surface transport, but the Oleander velocity data exhibit significant temporal variability principally due to a varying Ekman layer. Second, we compare Oleander and altimetry‐derived transport estimates with a set of oceanographic products (OSCAR, GLORYS12, GREPV2, ARMOR3D) as well as with transport estimates from hydrography. All agree with respect to surface transport reflecting the dominant influence of altimetry. Upper ocean (0–1,000 m) transports agree poorly except for acoustic Doppler current profiler estimates, and dynamic height. The analysis products give completely different results with respect to total (surface to bottom) transport. 

Abstract The surface-intensified, poleward-flowing Gulf Stream (GS) encounters the equatorward-flowing Deep Western Boundary Current (DWBC) at 36° N off Cape Hatteras. In this study, daily output from a data-assimilative, high-resolution (800 m), regional ocean reanalysis was examined to quantify variability in the velocity structure of the GS and DWBC during 2017–2018. The validity of this reanalysis was confirmed with independent observations of ocean velocity and density that demonstrate a high level of realism in the model’s representation of the regional circulation. The model’s daily velocity time series across a transect off Cape Hatteras was examined using rotated Empirical Orthogonal Function analysis, and analysis suggests three leading modes that characterize the variability of the western boundary currents throughout the water column. The first mode, related to meandering of the GS current, accounts for 55.3% of the variance, followed by a “wind-forced mode”, which accounts for 12.5% of the variance. The third mode, influenced by the DWBC and upper-ocean eddies, accounts for 7.1% of the variance. 

Abstract Science Research on Commercial Ships (Science RoCS) is a grassroots multi-institution group of scientists, engineers, data managers, and administrators seeking to further research opportunities by equipping commercial vessels with suites of maritime appropriate scientific sensors operated autonomously on regular ship routes with minimal crew intervention. Science RoCS aims to foster cooperation between the shipping industry and scientific community at a level that will be transformative for societally relevant ocean science, promote cross-disciplinary ocean science through simultaneous observation of the air/sea interface and water column, and spur a technological revolution in observational oceanography by developing new turnkey, maritime-industry-appropriate scientific equipment whose data streams can be used to stimulate innovations in oceanic (physical, chemical, and biological) understanding and forecasting. We envision a future where scientific data collection on commercial ships is the new industry standard, providing repeat measurements in undersampled, remote regions, on scales not otherwise accessible to the scientific community. 

{"Abstract":["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. <\/p>\n\nThe 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.    <\/p>\n\nLike 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.   <\/p>\n\nThe 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.  <\/p>\n\nNote 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.<\/strong><\/p>\n\nSince 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. <\/p>\n\nFurthermore, 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\u2019Errico, 2023). <\/p>\n\nEach monthly or annual GS path has 251 points between 75W to 50W at 0.1 degree resolution.  <\/p>"],"Other":["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."]}"]} 

{"Abstract":["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.   <\/p>\n\nAfter 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\u2019s 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. <\/p>\n\nThe 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). <\/p>\n\nCorresponding 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.   <\/p>\n\nThe 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.  <\/p>\n\nUnits 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. <\/p>\n\nFilenames: <\/p>\n\nmonthly_windstress_wsc_upwelling.nc<\/strong>: 480 time steps from 80W to 45W and 30N to 45N.<\/p>\n\nseasonal_windstress_wsc_upwelling.nc<\/strong>: 160 time steps from 80W to 45W and 30N to 45N.<\/p>\n\nannual_windstress_wsc_upwelling.nc<\/strong>: 40 time steps from 80W to 45W and 30N to 45N.<\/p>"],"Other":["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."]}"]}