Quantifying the mechanisms of tracer dispersion in the ocean remains a central question in oceanography, for problems ranging from nutrient delivery to phytoplankton, to the early detection of contaminants. Until now, most of the analysis has been based on Lagrangian concepts of transport, often focusing on the identification of features that minimize fluid exchange among regions, or more recently, on network tools which focus instead on connectivity and transport pathways. Neither of these approaches, however, allows us to rank the geographical sites of major water passage, and at the same time, to select them so that they monitor waters coming from separate parts of the ocean. These are instead key criteria when deploying an observing network. Here, we address this issue by estimating at any point the extent of the ocean surface which transits through it in a given time window. With such information we are able to rank the sites with major fluxes that intercept waters originating from different regions. We show that this allows us to optimize an observing network, where a set of sampling sites can be chosen for monitoring the largest flux of water dispersing out of a given region. When the analysis is performed backward in time, this method allows us to identify the major sources which feed a target region. The method is first applied to a minimalistic model of a mesoscale eddy field, and then to realistic satellite-derived ocean currents in the Kerguelen area. In this region, we identify the optimal location of fixed stations capable of intercepting the trajectories of 43 surface drifters, along with statistics on the temporal persistence of the stations determined in this way. We then identify possible hotspots of micro-nutrient enrichment for the recurrent spring phytoplanktonic bloom occurring here. Promising applications to other fields, such as larval connectivity, marine spatial planning or contaminant detection, are then discussed.
Crossroads of the mesoscale circulation
Baudena A.;
2019-01-01
Abstract
Quantifying the mechanisms of tracer dispersion in the ocean remains a central question in oceanography, for problems ranging from nutrient delivery to phytoplankton, to the early detection of contaminants. Until now, most of the analysis has been based on Lagrangian concepts of transport, often focusing on the identification of features that minimize fluid exchange among regions, or more recently, on network tools which focus instead on connectivity and transport pathways. Neither of these approaches, however, allows us to rank the geographical sites of major water passage, and at the same time, to select them so that they monitor waters coming from separate parts of the ocean. These are instead key criteria when deploying an observing network. Here, we address this issue by estimating at any point the extent of the ocean surface which transits through it in a given time window. With such information we are able to rank the sites with major fluxes that intercept waters originating from different regions. We show that this allows us to optimize an observing network, where a set of sampling sites can be chosen for monitoring the largest flux of water dispersing out of a given region. When the analysis is performed backward in time, this method allows us to identify the major sources which feed a target region. The method is first applied to a minimalistic model of a mesoscale eddy field, and then to realistic satellite-derived ocean currents in the Kerguelen area. In this region, we identify the optimal location of fixed stations capable of intercepting the trajectories of 43 surface drifters, along with statistics on the temporal persistence of the stations determined in this way. We then identify possible hotspots of micro-nutrient enrichment for the recurrent spring phytoplanktonic bloom occurring here. Promising applications to other fields, such as larval connectivity, marine spatial planning or contaminant detection, are then discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.