Abstract:

297 trajectories from near-surface CODE-type ocean drifters (drogued at a depth of one meter) tracked in real-time using SPOT GPS units, launched in the northern Gulf of Mexico near DeSoto Canyon in July 2012 as part of the CARTHE Grand Lagrangian Deployment (GLAD) experiment. Most of these drifters were launched as triplets (separated by roughly 100 meters at launch) in an attempt to measure multi-scale near surface dispersion. Positions are low-pass filtered (one hour cutoff period) and interpolated to uniform 15 minute intervals starting on whole hours over the period July 20 through October 22, 2012. No temperature or salinity sensors were attached to these drifters. This dataset was created by the Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE). This research was made possible by a grant from BP/The Gulf of Mexico Research Initiative.

Suggested Citation:

Özgökmen, Tamay. 2013. GLAD experiment CODE-style drifter trajectories (low-pass filtered, 15 minute interval records), northern Gulf of Mexico near DeSoto Canyon, July-October 2012. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N7VD6WC8

Publications:

Berta, M., Griffa, A., Magaldi, M. G., Özgökmen, T. M., Poje, A. C., Haza, A. C., & Olascoaga, M. J. (2012). Improved Surface Velocity and Trajectory Estimates in the Gulf of Mexico from Blended Satellite Altimetry and Drifter Data. Journal of Atmospheric and Oceanic Technology, 150904105051007. doi:10.1175/jtech-d-14-00226.1

Carrier, M. J., Ngodock, H., Smith, S., Jacobs, G., Muscarella, P., Ozgokmen, T., … Lipphardt, B. (2014). Impact of Assimilating Ocean Velocity Observations Inferred from Lagrangian Drifter Data Using the NCOM-4DVAR*. Monthly Weather Review, 142(4), 1509–1524. doi:10.1175/mwr-d-13-00236.1

Coelho, E. F., Hogan, P., Jacobs, G., Thoppil, P., Huntley, H. S., Haus, B. K., … Wei, M. (2015). Ocean current estimation using a Multi-Model Ensemble Kalman Filter during the Grand Lagrangian Deployment experiment (GLAD). Ocean Modelling, 87, 86–106. doi:10.1016/j.ocemod.2014.11.001

Jacobs, G. A., Bartels, B. P., Bogucki, D. J., Beron-Vera, F. J., Chen, S. S., Coelho, E. F., … Wei, M. (2014). Data assimilation considerations for improved ocean predictability during the Gulf of Mexico Grand Lagrangian Deployment (GLAD). Ocean Modelling, 83, 98–117. doi:10.1016/j.ocemod.2014.09.003

Muscarella, P., Carrier, M. J., Ngodock, H., Smith, S., Lipphardt, B. L., Kirwan, A. D., & Huntley, H. S. (2015). Do Assimilated Drifter Velocities Improve Lagrangian Predictability in an Operational Ocean Model? Monthly Weather Review, 143(5), 1822–1832. doi:10.1175/mwr-d-14-00164.1

Olascoaga, M. J., Beron-Vera, F. J., Haller, G., Triñanes, J., Iskandarani, M., Coelho, E. F., … Valle-Levinson, A. (2013). Drifter motion in the Gulf of Mexico constrained by altimetric Lagrangian coherent structures. Geophysical Research Letters, 40(23), 6171–6175. doi:10.1002/2013gl058624

Poje, A. C., Ozgokmen, T. M., Lipphardt, B. L., Haus, B. K., Ryan, E. H., Haza, A. C., … Mariano, A. J. (2014). Submesoscale dispersion in the vicinity of the Deepwater Horizon spill. Proceedings of the National Academy of Sciences, 111(35), 12693–12698. doi:10.1073/pnas.1402452111

Yaremchuk, M., & Coelho, E. F. (2015). Filtering Drifter Trajectories Sampled at Submesoscale Resolution. IEEE J. Oceanic Eng., 40(3), 497–505. doi:10.1109/joe.2014.2353472

Curcic, M., Chen, S. S., & Özgökmen, T. M. (2016). Hurricane-induced ocean waves and stokes drift and their impacts on surface transport and dispersion in the Gulf of Mexico. Geophysical Research Letters, 43(6), 2773–2781. doi:10.1002/2015gl067619

Mariano, A. J., Ryan, E. H., Huntley, H. S., Laurindo, L. C., Coelho, E., Griffa, A., … Wei, M. (2016). Statistical properties of the surface velocity field in the northern Gulf of Mexico sampled by GLAD drifters. Journal of Geophysical Research: Oceans, 121(7), 5193–5216. doi:10.1002/2015jc011569

Beron-Vera, F. J., & LaCasce, J. H. (2016). Statistics of Simulated and Observed Pair Separations in the Gulf of Mexico. Journal of Physical Oceanography, 46(7), 2183–2199. doi:10.1175/jpo-d-15-0127.1

Berta, M., Griffa, A., Özgökmen, T. M., & Poje, A. C. (2016). Submesoscale evolution of surface drifter triads in the Gulf of Mexico. Geophysical Research Letters, 43(22), 11,751–11,759. doi:10.1002/2016gl070357

Miron, P., Beron-Vera, F. J., Olascoaga, M. J., Sheinbaum, J., Pérez-Brunius, P., & Froyland, G. (2017). Lagrangian dynamical geography of the Gulf of Mexico. Scientific Reports, 7(1). doi:10.1038/s41598-017-07177-w

Duran, R., Beron-Vera, F. J., & Olascoaga, M. J. (2018). Extracting quasi-steady Lagrangian transport patterns from the ocean circulation: An application to the Gulf of Mexico. Scientific Reports, 8(1). doi:10.1038/s41598-018-23121-y

Olascoaga, M. J., Miron, P., Paris, C., Pérez-Brunius, P., Pérez-Portela, R., Smith, R. H., & Vaz, A. (2018). Connectivity of Pulley Ridge with remote locations as inferred from satellite-tracked drifter trajectories. Journal of Geophysical Research: Oceans. doi:10.1029/2018jc014057

Gough, M. K., Beron-Vera, F. J., Olascoaga, M. J., Sheinbaum, J., Jouanno, J., & Duran, R. (2019). Persistent Lagrangian Transport Patterns in the Northwestern Gulf of Mexico. Journal of Physical Oceanography, 49(2), 353–367. doi:10.1175/jpo-d-17-0207.1

Poje, A. C., Özgökmen, T. M., Bogucki, D. J., & Kirwan, A. D. (2017). Evidence of a forward energy cascade and Kolmogorov self-similarity in submesoscale ocean surface drifter observations. Physics of Fluids, 29(2), 020701. doi:10.1063/1.4974331

Novelli, G., Guigand, C. M., Boufadel, M. C., & Özgökmen, T. M. (2020). On the transport and landfall of marine oil spills, laboratory and field observations. Marine Pollution Bulletin, 150, 110805. doi:10.1016/j.marpolbul.2019.110805

Berta, M., Griffa, A., Haza, A. C., Horstmann, J., Huntley, H. S., Ibrahim, R., … Poje, A. C. (2020). Submesoscale Kinematic Properties in Summer and Winter Surface Flows in the Northern Gulf of Mexico. Journal of Geophysical Research: Oceans, 125(10). doi:10.1029/2020jc016085

Carrier, M. J., Ngodock, H. E., Muscarella, P., & Smith, S. (2016). Impact of Assimilating Surface Velocity Observations on the Model Sea Surface Height Using the NCOM-4DVAR*. Monthly Weather Review, 144(3), 1051–1068. doi:10.1175/mwr-d-14-00285.1

Purpose:

Triads of CODE style drifters (initially separated by roughly 100 meteres) were launched nearly simultaneously to measure near-surface relative dispersion over scales ranging from 100 meters to 100 km.

Data Parameters and Units:

Column 1: drifter ID string (like CARTHE_XXX, XXX=3 digit integer) Column 2: date (yyyy-mm-dd) Column 3: time (HH:MM:SS.SS) Column 4: latitude (decimal degrees) Column 5: longitude (decimal degrees) Column 6: estimated position error (meters) Column 7: u (east-west) velocity (m/sec) Column 8: v (north-south) velocity (m/sec) Column 9: estimated velocity error (m/sec)

Methods:

GLAD CODE drifter positions were reported in real-time roughly every five minutes via the Globalstar satellite network. Positions reported by the SPOT handheld GPS units inside each drifter were nominally accurate to within seven meters. Occasionally, position errors much larger than this nominal value are found. These may be due to errors in GPS baselines (due to poor satellite reception), data dropout, and, in some cases, drifters that were picked up by small boats. Each drifter record ends when the drifter was known to be picked up by a boat, when the signal was lost for more than 24 hours, or when the drifter traveled more than 80 km in a 12 hours period (implying a mean speed of 1.85 m/sec over 12 hours). For each record, positions that imply an instantaneous drifter speed greater than 3 m/sec were deleted. Also, positions that imply the drifter track rotated through more than 360 compass degrees within three hours were deleted. Next, outliers were identified as positions that were more than 100 meters away from estimated positions at the same times interpolated from a set of both past and future positions. These outliers were deleted. All valid positions were then interpolated to uniform, five-minute time intervals using spline interpolation. These five-minute records were used to compute finite difference estimates of u (east-west) and v (north-south) velocities. Finally, the five-minute position and velocity records were filtered using a Butterworth fourth-order low-pass filter with a one hour period cutoff. These low-pass filtered records were then interpolated to uniform 15-minute intervals beginning on whole hours. Crude estimates of position error are also provided for each position in the final 15-minute interval records. The error was set to 10 meters (a nominal value) for positions recorded at times for which there were no gaps in the five-minute raw data records over the previous hour. The error was increased according to the ratio of the average sample time interval for the previous 12 raw data positions to the nominal sample interval of 5 minutes, multiplied by the 10 meter nominal error value. Velocity errors were computed by dividing the sum of two consecutive position errors by the corresponding time interval.

Instruments:

CODE II drifter body with SPOT Satellite GPS Messenger (orange).

Individual Files: