de Verneil A., Rousselet L., Doglioli A. M., Petrenko A. A., Maes Christophe, Bouruet-Aubertot P., Moutin T. (2018). OUTPACE long duration stations : physical variability, context of biogeochemical sampling, and evaluation of sampling strategy. Biogeosciences, 15 (7), p. 2125-2147. ISSN 1726-4170.
Titre du document
OUTPACE long duration stations : physical variability, context of biogeochemical sampling, and evaluation of sampling strategy
de Verneil A., Rousselet L., Doglioli A. M., Petrenko A. A., Maes Christophe, Bouruet-Aubertot P., Moutin T.
Source
Biogeosciences, 2018,
15 (7), p. 2125-2147 ISSN 1726-4170
Research cruises to quantify biogeochemical fluxes in the ocean require taking measurements at stations lasting at least several days. A popular experimental design is the quasi-Lagrangian drifter, often mounted with in situ incubations or sediment traps that follow the flow of water over time. After initial drifter deployment, the ship tracks the drifter for continuing measurements that are supposed to represent the same water environment. An outstanding question is how to best determine whether this is true. During the Oligotrophy to UlTra-oligotrophy PACific Experiment (OUTPACE) cruise, from 18 February to 3 April 2015 in the western tropical South Pacific, three separate stations of long duration (five days) over the upper 500m were conducted in this quasi-Lagrangian sampling scheme. Here we present physical data to provide context for these three stations and to assess whether the sampling strategy worked, i.e., that a single body of water was sampled. After analyzing tracer variability and local water circulation at each station, we identify water layers and times where the drifter risks encountering another body of water. While almost no realization of this sampling scheme will be truly Lagrangian, due to the presence of vertical shear, the depth-resolved observations during the three stations show most layers sampled sufficiently homogeneous physical environments during OUTPACE. By directly addressing the concerns raised by these quasi-Lagrangian sampling platforms, a protocol of best practices can begin to be formulated so that future research campaigns include the complementary datasets and analyses presented here to verify the appropriate use of the drifter platform.
