Shelf, shear and staircases: glider observations in the North Atlantic

Ocean gliders have established themselves as a key component of the Global Ocean Observing System. Gliders are particularly useful in shelf-break areas that cannot be surveyed by profiling floats, such as those of the Argo program. This thesis uses a legacy glider dataset to examine shelf break processes in an upwelling zone. This dataset covers two periods of upwelling over the NW Iberian margin in summer 2010. During this deployment, equatorward transport was maintained over the shelf for 70 days during one of the strongest upwelling seasons on record. The use of gliders to collect temperature and salinity profiles for extended periods of time is well established. This thesis examines two new technologies that have recently been applied to gliders: acoustic Doppler current profilers (ADCPs) and automated classification algorithms. The integration of a 1~MHz ADCP into a Seaglider is described, along with the tests, trials, and results of four deployments. The challenges of this sensor integration are explored, with recommendations made for future use of the glider and suggested improvements to the ADCP. This work includes the production of a user manual for future users of the ADCP glider. Using a dataset collected by three gliders in the tropical North Atlantic, a new algorithm for identifying thermohaline staircases in glider data is described. Applying this algorithm, over 14000 thermohaline steps are identified in profiles from the three gliders. It is hypothesised that the incidence of thermohaline staircases is limited by strong background gradients in conservative temperature and absolute salinity. Additionally, fast-response thermistor data are used to examine the sensitivity of automated thermohaline staircase classifiers to the vertical resolution of temperature and salinity profiles

Glider observations of thermohaline staircases in the tropical North Atlantic using an automated classifier

Thermohaline staircases are stepped structures of alternating thick mixed layers and thin high-gradient interfaces. These structures can be up to several tens of metres thick and are associated with double-diffusive mixing. Thermohaline staircases occur across broad swathes of the Arctic and tropical and subtropical oceans and can increase rates of diapycnal mixing by up to 5 times the background rate, driving substantial nutrient fluxes to the upper ocean. In this study, we present an improved classification algorithm to detect thermohaline staircases in ocean glider profiles. We use a dataset of 1162 glider profiles from the tropical North Atlantic collected in early 2020 at the edge of a known thermohaline staircase region. The algorithm identifies thermohaline staircases in 97.7 % of profiles that extend deeper than 300 m. We validate our algorithm against previous results obtained from algorithmic classification of Argo float profiles. Using fine-resolution temperature data from a fast-response thermistor on one of the gliders, we explore the effect of varying vertical bin sizes on detected thermohaline staircases. Our algorithm builds on previous work by adding improved flexibility and the ability to classify staircases from profiles with noisy salinity data. Using our results, we propose that the incidence of thermohaline staircases is limited by strong background vertical gradients in conservative temperature and absolute salinity.</p

Glider Observations of Thermohaline Staircases in the Tropical North Atlantic Using an Automated Classifier

Thermohaline staircases are stepped structures of alternating thick mixed layers and thin high gradient interfaces. These structures can be up to several tens of metres thick and are associated with double-diffusive mixing. Thermohaline staircases occur across broad swathes of the Arctic and tropical/subtropical oceans and can increase rates of diapycnal mixing by up to five times the background rate, driving substantial nutrient fluxes to the upper ocean. In this study, we present an improved classification algorithm to detect thermohaline staircases in ocean glider profiles. We use a dataset of 1162 glider profiles from the tropical North Atlantic collected in early 2020 at the edge of a known thermohaline staircase region. The algorithm identifies thermohaline staircases in 97.7 % of profiles that extend deeper than 300 m. We validate our algorithm against previous results obtained from algorithmic classification of Argo float profiles. Using fine resolution temperature data from a fast-response thermistor on one of the gliders, we explore the effect of varying vertical bin sizes on detected thermohaline staircases. Our algorithm builds on previous work with improved flexibility and the ability to classify staircases from profiles with poor salinity data. Using our results, we propose that the incidence of thermohaline staircases is limited by strong background vertical gradients in conservative temperature and absolute salinity

Glider Observations of the Northwestern Iberian Margin During an Exceptional Summer Upwelling Season

Glider observations from the Northwestern Iberian Margin during the exceptionally strong 2010 summer upwelling season resolved the evolution of physical and biogeochemical variables during two upwelling events. Upwelling brought low-oxygen Eastern North Atlantic Central Water from 190 m depth onto the shelf up to a depth of 50 m. During the two observed periods of upwelling, a poleward jet developed over the shelf break. The persistent upwelling favorable winds maintained equatorward flow on the outer shelf for 2 months with no reversals during relaxation periods, a phenomenon not previously observed. During upwelling, near-surface chlorophyll a concentration increased by more than 6 mg m −3. Oxygen supersaturation in the near surface increased by more than 20%, 6 days after the chlorophyll a maximum

test data for gliderad2cp

Data files used for the demonstration and testing of the gliderad2cp library https://github.com/bastienqueste/gliderad2c

test data for gliderad2cp

Data files used for the demonstration and testing of the gliderad2cp library https://github.com/bastienqueste/gliderad2c

Ocean cross-validated observations from R/Vs L'Atalante, Maria S. Merian, and Meteor and related platforms as part of the EUREC⁴A-OA/ATOMIC campaign

The northwestern Tropical Atlantic Ocean is a turbulent region, filled with mesoscale eddies and regional currents. In this intense dynamical context, several water masses with thermohaline characteristics of different origins are advected, mixed, and stirred at the surface and at depth. The EUREC4A-OA/ATOMIC experiment that took place in January and February 2020 was dedicated to assessing the processes at play in this region, especially the interaction between the ocean and the atmosphere. For that reason, four oceanographic vessels and different autonomous platforms measured properties near the air–sea interface and acquired thousands of upper-ocean (up to 400–2000 m depth) profiles. However, each device had its own observing capability, varying from deep measurements acquired during vessel stations to shipboard underway near-surface observations and measurements from autonomous and uncrewed systems (such as Saildrones). These observations were undertaken with a specific sampling strategy guided by near-real-time satellite maps and adapted every half day, based on the process that was investigated. These processes were characterized by different spatiotemporal scales, from mesoscale eddies, with diameters exceeding 100 km, to submesoscale filaments of 1 km width. This article describes the datasets gathered from the different devices and how the data were calibrated and validated. In order to ensure an overall consistency, the platforms' datasets are cross-validated using a hierarchy of instruments defined by their own specificity and calibration procedures. This has enabled the quantification of the uncertainty in the measured parameters when different datasets are used together, e.g., https://doi.org/10.17882/92071 (L'Hégaret et al., 2020a)