Lagrangian drifters in the San Matias Gulf, Argentina

DOI

Five SVP-type Lagrangian drifters were launched in the positions indicated in Fig. 2 (see also Table 1) on January 31, 2019. Each drifter was composed by a buoy anchored at 15m. The anchor consisted of four triangular fabrics attached symmetrically along its largest leg and to two iron bars along their shortest leg. The ratio between the drag corresponding to the portion of the buoy that remains above the surface of the sea and the drag corresponding to everything that is below the water is 50. Thus, the drifters employed exceed the drag ratio recommended for this type of buoys to minimize downwind slippage (Ciarravano et al. 2012). Inside the buoy we installed a GPS with satellite communication. The GPS was set to send its position in real time every 10 minutes.  Drifter 04 is the one that lasted longer sending its position for 22.6 days (Table 1). Drifter 02 was accidentally recovered 3 days after deployment by a fisherman. The other three drifters lasted 1.9, 6.8 and 7.4 days. For the five drifters, the percentage of total amount of data collected was lower than the ideal one (up to 27.6% of missing data), however a minimum of 7 positions every six hours were successfully retrieved (Table 1). Failure in the transmission of the data might occur for a number of different reasons, including weather conditions, wave height and failure in the satellite connection, among others. Despite their short duration, and thanks to the high-frequency transmission of the positions, the data collected provided very reach and accurate information about the surface circulation of the region.

Identifier
DOI https://doi.org/10.17882/74297
Metadata Access http://www.seanoe.org/oai/OAIHandler?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:seanoe.org:74297
Provenance
Creator Saraceno, Martin; Aubone, Nicolas; Saad, Juan Francisco; Soria, Mariano; Svendsen, Guillermo
Publisher SEANOE
Publication Year 2019
Rights CC0
OpenAccess true
Contact SEANOE
Representation
Resource Type Dataset
Discipline Marine Science