Glider Mission Research Articles

Machine learning-based semi-online performance optimisation for long-range underwater glider missions

Machine learning-based semi-online performance optimisation for long-range underwater glider missions

On the Seasonal Cycle of Phytoplankton Bio‐Optical Properties Inside a Warm Core Ring in the Gulf of Mexico

AbstractFour underwater glider missions were carried out to sample the physical and bio‐optical properties inside a Loop Current Eddy (LCE) in the Gulf of Mexico, to investigate whether the winter deepening of the mixed‐layer and erosion of the nitracline stimulates phytoplankton growth. Recent coupled physical‐biogeochemical numerical models support this mechanism, but observations using profiling floats suggest that there is no seasonal cycle on integrated phytoplankton biomass. Here, data collected by underwater gliders during a full seasonal cycle and inside the LCE Poseidon support the idea of an increase in phytoplankton biomass during winter, consistent with nutrient entrainment into the euphotic zone. The changes in fluorescence emission per chlorophyll‐a unit and their implications for interpreting bio‐optical variability were also assessed. Linear regressions between in vivo chlorophyll‐a fluorescence and satellite chlorophyll‐a concentration show the largest (smallest) slopes during winter (summer), suggesting a shift in the phytoplankton community along the year or photoacclimation. Although the glider data set is convolved by temporal and spatial variability, and chlorophyll‐a fluorescence is affected by multiple factors, the concomitant enhancement of particle backscattering coefficient and chlorophyll‐a observed during winter supports the occurrence of a seasonal cycle in phytoplankton biomass. Deep vertical mixing in winter inside the core of the LCE, can promote fertilization through vertical diffusion of nutrients. Poseidon was an extraordinary, large, and strong, LCE that prompted phytoplankton blooms in winter highlighting their relevance for primary production and in general for biogeochemical processes.

Circulation and Hydrography in the Northwestern Barents Sea: Insights From Recent Observations and Historical Data (1950–2022)

AbstractThe Barents Sea is one of the main pathways for warm and saline Atlantic Water (AW) entering the Arctic Ocean. It is an important region where water mass transformation and dense‐water production contribute to the Atlantic meridional overturning circulation. Here, we present data from three cruises and nine glider missions conducted between 2019 and 2022 in the northwestern Barents Sea, and compare them with historical data collected between 1950 and 2009. We present circulation pathways, hydrography and volume transports of Atlantic‐ and Arctic‐origin waters. Our observations show that 0.9 ± 0.1 Sv (1 Sv = 106 m3 s−1) of Atlantic‐origin water reaches the Polar Front (PF) region before splitting into several branches and eventually subducting beneath Polar Water (PW). The amount of Atlantic‐origin water stored in the Olga Basin north of the PF is controlled by the density difference between AW and PW, and reached a maximum in the 90s when PW was particularly fresh. In the recent period from 2019 to 2022, the inflow of AW into the Barents Sea freshened by up to 0.1 g kg−1 compared to previous decades. This led to a reduction in the production of dense water, an increased temperature gradient across the PF, and a reduced poleward transport of warm water.

Risk analysis and assessment of underwater glider mission failure using Dynamic Bayesian Network method

The Autonomous Underwater Glider (AUG), with its extended operational endurance, encounters various uncertain risks during diverse mission tasks. Therefore, conducting dynamic risk analysis is crucial for implementing subsequent decisions and improving equipment safety. This paper combines Fault Tree Analysis (FTA) and Dynamic Bayesian Network (DBN) to develop a customized dynamic risk assessment method for AUG task failure under multiple risk factors. Firstly, preliminary risk factors are identified by FTA using existing experimental data. Next, transformation rules are constructed to map FTA into a basic DBN model. Then, parameters such as conditional probabilities are determined through logic gates and parameter learning, and the proposed model is validated based on axioms. Finally, key risk factors are identified based on actual failure data. The research results indicate that the key risk factors leading to AUG task failure are progressive abnormalities such as biofouling and ocean current disturbance. The method proposed in this paper can achieve dynamic risk assessment, providing strong references for operators in making decisions for subsequent tasks.

A data-driven approach for predicting depth-averaged velocities in the early stages of underwater glider navigation

Predicting the depth-averaged velocities of underwater gliders in the early stages of navigation is crucial for task performance optimization. However, due to the insufficient number of data samples for the depth-averaged velocities of underwater gliders in the early stages of navigation and the complex mechanisms of depth-averaged flow, task performance optimization remains challenging. This study presents a data-driven approach, the CutMix-augmented Extreme Gradient Boosting (CM_XGB) method, to effectively address this issue. Initially, the CutMix method is employed to augment the depth-averaged velocity samples. Then, the XGB method is applied for prediction. The proposed CM_XGB method is compared to five different prediction methods using three real-world depth-averaged velocity datasets and three error evaluation metrics, and its effectiveness in accurately predicting depth-averaged velocities under the same parameter conditions during the early stages of observation missions is demonstrated. This study shows that the CM_XGB method accurately predicts depth-averaged velocities even with limited data. This method is especially useful for underwater glider missions with data challenges in the initial stages. The success of the CM_XGB method highlights its potential for broader applications in oceanographic research and related fields, providing a valuable tool for scientists and researchers working with limited datasets.

Quantifying coastal freshwater extremes during unprecedented rainfall using long timeseries multi-platform salinity observations

During 2022, extreme rainfall occurred across southeast Australia, making it the wettest year on record. The oceanic impact of extreme rainfall events in normally ‘dry’ regions is not well understood, as their effects are challenging to observe. Here, we use unique multi-platform timeseries and spatial data from 36 autonomous ocean glider missions over 13 years, and we define an extreme salinity threshold inshore of the East Australian Current. We show that the freshwater plume extended fivefold further than previously thought. The compound effect of multiple large rainfall events resulted in a newly observed stratification (‘double-stacking’) dynamic, with the stratification being largely controlled by salinity. Extreme salinity events are known to be important for species composition of local fisheries as well as detrimental for coastal water quality. Such events and their impacts may become more common as extreme rainfall events are projected to become more frequent in a changing climate. Hence, comprehensive observing strategies facilitating identification of salinity extremes are essential.

Hydrography and deep chlorophyll maximum patterns of the Athos Basin and the Thracian Sea continental shelf (North Aegean Sea) combining glider and satellite observations

This work focuses on the North Aegean Sea deep chlorophyll maximum (DCM) dynamics, as revealed during the first glider mission over the continental shelf and slope of the Thracian Sea and along the Athos basin, and presents a conceptual model on the response of the DCM in relation to the prevailing stratification/mixing of the water column. Water temperature, conductivity, salinity, chlorophyll-a, CDOM, DO and particle backscatter data (bb700), were recorded during this underwater glider mission in summer 2019. Daily satellite data from Sentinel 3 complemented the glider collected data to validate the satellite-derived estimates of surface Chlorophyll-a levels. The high-resolution physical and chemical observations were analyzed emphasizing on thermal stratification, pycnocline strength, CDOM and dissolved oxygen vertical distribution and the presence of deep chlorophyll maximum (DCM). DCM statistical characteristics were derived by fitting a Gaussian model on the chlorophyll-a profiles. The mean DCM was observed at 76 ± 14.5 m depth, located below the euphotic layer, estimated at 64 ± 2.1 m, with the water column dynamics affecting directly its depth, thickness and peak prominence. The satellite-derived chlorophyll-a, integrated within the euphotic layer, was found in fair agreement to the integrated chlorophyll-a values from surface to optical depth recorded by the glider. Chl-a at the DCM were found up to 0.60 mg m−3, the vertically-integrated pigment content was estimated at 45 ± 14 mg m−2 and the values of Optical Community Index (OCI) illustrate the dominance of small-sized plankton. The increased variability in the particulate backscattering coefficient bb700 in Thracian Sea shelf and slope deep waters seems related to sediment resuspension. CDOM levels increased from 0.76 ppb at the sea surface to 1.11 ppb at 40 m depth, being positively correlated to Chl-a within the DCM. CDOM concentration increased steadily at intermediate and deeper waters up to 1.34 ± 0.07 ppb. DO profiles revealed the presence of an oxycline in the DCM layer, capable to oxygenate the intermediate and deeper waters (+3 × 10−3 ml/L/m). Bottom DO in Athos basin was measured at 5.0 ml L−1, indicating that the apparent oxygen utilization in Athos Basin is approximately 50 μmol L−1.

K nearest neighbors classification of water masses in the western Alboran Sea using the sigma-pi diagram

Different classification techniques of water masses have been developped using the potential temperature-salinity (θ-S) diagram and its volumetric analysis. In this study, we propose a new method to automatically classify water masses via a supervised machine learning algorithm based on the K nearest neighbors (Knn), in the potential density and potential spicity (σ-π) coordinates. This method is applied to temperature and salinity data collected in the western side of the Alboran Sea during a glider mission, dedicated to sample the Western Alboran Gyre (WAG) in late winter 2021. The water masses in the studied region were classified into five different categories following a supervised learning process, based on ocean profile databases available on the region of interest. The results corroborate previous studies of the spatial distribution of water masses in the Alboran Sea, inferred from traditional method based on the expert analysis of the (θ-S) diagram, and suggest that this methodology is efficient and reliable for water masses classification. Compared to a classical clustering computation (herein k-means), this method is more appropriate in a region where the characteristics of the water masses change considerably in both space and time.

Gliders for passive acoustic monitoring of the oceanic environment

Ocean gliders are quiet, buoyancy-driven, long-endurance, profiling autonomous platforms. Gliders therefore possess unique advantages as platforms for Passive Acoustic Monitoring (PAM) of the marine environment. In this paper, we review available glider platforms and passive acoustic monitoring systems, and explore current and potential uses of passive acoustic monitoring-equipped gliders for the study of physical oceanography, biology, ecology and for regulatory purposes. We evaluate limiting factors for passive acoustic monitoring glider surveys, such as platform-generated and flow noise, weight, size and energy constraints, profiling ability and slow movement. Based on data from 34 passive acoustic monitoring glider missions, it was found that <13% of the time spent at sea was unsuitable for passive acoustic monitoring measurements, either because of surface communications or glider manoeuvre, leaving the remainder available for subsequent analysis. To facilitate the broader use of passive acoustic monitoring gliders, we document best practices and include workarounds for the typical challenges of a passive acoustic monitoring glider mission. Three research priorities are also identified to improve future passive acoustic monitoring glider observations: 1) Technological developments to improve sensor integration and preserve glider endurance; 2) improved sampling methods and statistical analysis techniques to perform population density estimation from passive acoustic monitoring glider observations; and 3) calibration of the passive acoustic monitoring glider to record absolute noise levels, for anthropogenic noise monitoring. It is hoped this methodological review will assist glider users to broaden the observational capability of their instruments, and help researchers in related fields to deploy passive acoustic monitoring gliders in their studies.

A simulator of underwater glider missions for path planning

A simulator of underwater glider missions for path planning

Submesoscale variability in a mesoscale front captured by a glider mission in the Gulf of Finland, Baltic Sea

Modern research methods enable unfolding the structure of the water column with higher resolution than ever, revealing the importance of submesoscale. Submesoscale processes have intermediate space and time scales of <5 km and a few days in the Baltic Sea. A glider mission was conducted in the Gulf of Finland in May 2018. The appearance of a mesoscale front as a response to the persisting NE–E winds was observed. Within the front, smaller scale features at a lateral scale of a km were apparent. The tracer patterns indicated the presence of two adjacent motions – cold (warm) water penetrating upward (downward) on the lighter (denser) side of the front. We suggest they were traces of ageostrophic secondary circulation emerging while the loss of the upwelling-favorable forcing arrested the strengthening of the front. The analysis showed favorable conditions for the baroclinic and wind-driven instability. Such circulations could work to equalize the differences in cross-front direction, affecting the stratification and acting against the persistence of the mesoscale front. The spatial spectra of isopycnal tracer variance revealed the depth-dependence of the spectral slopes at the lateral scales of 1–10 km in the upper part of the water column. The differing of the slopes in the density layers associated with the mesoscale front indicates that frontal dynamics contribute to the energy cascade.

The occurrence of humpback whales across the Hawaiian archipelago revealed by fixed and mobile acoustic monitoring

The occurrence of humpback whales (Megaptera novaeangliae) across the 2600 km of Hawaiian archipelago, which include the remote atolls, banks, and seamounts of Papahānaumokuākea Marine National Monument (PMNM), remains poorly understood. Previous surveys for humpback whales beyond the main Hawaiian Islands have been scarce due to limited access and the challenging winter conditions typically found in PMNM when whales are present. To overcome these limitations, a combination of moored acoustic recorders and a Wave Glider autonomous surface vehicle were used to acoustically monitor eight locations and survey approximately 1500 km of the Hawaiian archipelago for the occurrence of humpback whale song during the 2019-2020 breeding season. Relative song prevalence was established using a machine learning tool and by quantifying the level of song chorusing. A generalized additive model framework was applied to understand the associations between habitat variables and humpback whale song occurrence, and sound propagation modeling was performed to examine whether acoustic propagation influenced observed patterns. Whale song was recorded at all monitored and surveyed locations across the archipelago, albeit in varying amounts. Among the locations monitored with moored recorders, the highest and most sustained seasonal chorusing levels were measured off Maui followed by French Frigate Shoals (Kānemilohai), Hawaii Island, Middle Bank, Oahu, Kauai, Gardner Pinnacles (Pūhāhonu) and Pearl and Hermes Reef (Holoikauaua), respectively. The Wave Glider mission to PMNM revealed that song prevalence was highest at Middle Bank and gradually decreased further to the northwest, reaching a minimum at Gardner Pinnacles (Pūhāhonu). However, song occurrence increased again at Raita Bank, remaining high between Raita Bank and the Northampton Seamounts. The results reveal that nearly the entire Hawaiian archipelago is exploited by humpback whales during the winter and early spring months. Moreover, song occurrence patterns suggest that there may be more structure in the distribution of whales in PMNM than previously known and raises questions about whether multiple subpopulations occur across the archipelago.

Net community production in the northwestern Mediterranean Sea from glider and buoy measurements

Abstract. The Mediterranean Sea comprises just 0.8 % of the global oceanic surface, yet considering its size, it is regarded as a disproportionately large sink for anthropogenic carbon due to its physical and biogeochemical characteristics. An underwater glider mission was carried out in March–April 2016 close to the BOUSSOLE and DyFAMed time series moorings in the northwestern Mediterranean Sea. The glider deployment served as a test of a prototype ion-sensitive field-effect transistor pH sensor. Dissolved oxygen (O2) concentrations and optical backscatter were also observed by the glider and increased between 19 March and 1 April, along with pH. These changes indicated the start of a phytoplankton spring bloom, following a period of intense mixing. Concurrent measurements of CO2 fugacity and O2 concentrations at the BOUSSOLE mooring buoy showed fluctuations, in qualitative agreement with the pattern of glider measurements. Mean net community production rates (N) were estimated from glider and buoy measurements of dissolved O2 and inorganic carbon (DIC) concentrations, based on their mass budgets. Glider and buoy DIC concentrations were derived from a salinity-based total alkalinity parameterisation, glider pH and buoy CO2 fugacity. The spatial coverage of glider data allowed the calculation of advective O2 and DIC fluxes. Mean N estimates for the euphotic zone between 10 March and 3 April were (-17±36) for glider O2, (44±94) for glider DIC, (17±37) for buoy O2 and (49±86) mmolm-2d-1 for buoy DIC, all indicating net metabolic balance over these 25 d. However, these 25 d were actually split into a period of net DIC increase and O2 decrease between 10 and 19 March and a period of net DIC decrease and O2 increase between 19 March and 3 April. The latter period is interpreted as the onset of the spring bloom. The regression coefficients between O2 and DIC-based N estimates were 0.25 ± 0.08 for the glider data and 0.54 ± 0.06 for the buoy, significantly lower than the canonical metabolic quotient of 1.45±0.15. This study shows the added value of co-locating a profiling glider with moored time series buoys, but also demonstrates the difficulty in estimating N, and the limitations in achievable precision.

Eddy Vertical Structure and Variability: Deepglider Observations in the North Atlantic

Abstract Hundreds of full-depth temperature and salinity profiles collected by Deepglider autonomous underwater vehicles (AUVs) in the North Atlantic reveal robust signals in eddy isopycnal vertical displacement and horizontal current throughout the entire water column. In separate glider missions southeast of Bermuda, subsurface-intensified cold, fresh coherent vortices were observed with velocities exceeding 20 cm s−1 at depths greater than 1000 m. With vertical resolution on the order of 20 m or less, these full-depth glider slant profiles newly permit estimation of scaled vertical wavenumber spectra from the barotropic through the 40th baroclinic mode. Geostrophic turbulence theory predictions of spectral slopes associated with the forward enstrophy cascade and proportional to inverse wavenumber cubed generally agree with glider-derived quasi-universal spectra of potential and kinetic energy found at a variety of locations distinguished by a wide range of mean surface eddy kinetic energy. Water-column average spectral estimates merge at high vertical mode number to established descriptions of internal wave spectra. Among glider mission sites, geographic and seasonal variability implicate bottom drag as a mechanism for dissipation, but also the need for more persistent sampling of the deep ocean. Significance Statement Relative to upper-ocean measurements of temperature, salinity, and velocity, deep ocean measurements (below 2000 m) are fewer in number and more difficult to collect. Deep measurements are needed, however, to explore the nature of deep ocean circulation contributing to the global redistribution of heat and to determine how upper-ocean behavior impacts or drives deep motions. Understanding of geographic and temporal variability in vertical structures of currents and eddies enables improved description of energy pathways in the ocean driven by turbulent interactions. In this study, we use newly developed autonomous underwater vehicles, capable of diving to the seafloor and back on a near daily basis, to collect high-resolution full ocean depth measurements at various locations in the North Atlantic. These measurements reveal connections between surface and deep motions, and importantly show their time evolution. Results of analyzing these vertical structures reveal the deep ocean to regularly “feel” events in the upper ocean and permit new comparisons to deep motions in climate models.

Air-Sea Gas Fluxes and Remineralization From a Novel Combination of pH and O2 Sensors on a Glider

Accurate, low-power sensors are needed to characterize biogeochemical variability on underwater glider missions. However, the needs for high accuracy and low power consumption can be difficult to achieve together. To overcome this difficulty, we integrated a novel sensor combination into a Seaglider, comprising a spectrophotometric lab-on-a-chip (LoC) pH sensor and a potentiometric pH sensor, in addition to the standard oxygen (O2) optode. The stable, but less frequent (every 10 min) LoC data were used to calibrate the high-resolution (1 s) potentiometric sensor measurements. The glider was deployed for a 10-day pilot mission in August 2019. This represented the first such deployment of either type of pH sensor on a glider. The LoC pH had a mean offset of +0.005±0.008 with respect to pH calculated from total dissolved inorganic carbon content, c(DIC), and total alkalinity, AT, in co-located water samples. The potentiometric sensor required a thermal-lag correction to resolve the pH variations in the steep thermocline between surface and bottom mixed layers, in addition to scale calibration. Using the glider pH data and a regional parameterization of AT as a function of salinity, we derived the dissolved CO2 content and glider c(DIC). Glider surface CO2 and O2 contents were used to derive air-sea fluxes, Φ(CO2) and Φ(O2). Φ(CO2) was mostly directed into the ocean with a median of −0.4 mmol m–2 d–1. In contrast, Φ(O2) was always out of the ocean with a median of +40 mmol m–2 d–1. Bottom water apparent oxygen utilization (AOU) was (35±1) μmol kg–1, whereas apparent carbon production (ACP) was (11±1) μmol kg–1, with mostly insignificant differences along the deployment transect. This deployment shows the potential of using pH sensors on autonomous observing platforms such as Seagliders to quantify the interactions between biogeochemical processes and the marine carbonate system at high spatiotemporal resolution.

Observation, Preconditioning and Recurrence of Exceptionally High Salinities in the Adriatic Sea

The paper aims to describe the preconditioning and observations of exceptionally high salinity values that were observed in summer and autumn of 2017 in the Adriatic. The observations encompassed CTD measurements carried out along the well-surveyed climatological transect in the Middle Adriatic (the Palagruža Sill, 1961–2020), Argo profiling floats and several glider missions, accompanied with satellite altimetry and operational ocean numerical model (Mediterranean Forecasting System) products. Typically, subsurface salinity maximum, with values lower than 39.0, is observed in the Southern Adriatic (usually between 200 and 400 m), related to ingressions of saltier and warmer waters originating in the eastern Mediterranean (Levantine Intermediate Water—LIW). However, seasonally strong inflow of warm and high salinity waters (S > 38.8) has been observed much closer to the surface since spring 2015. The main LIW core deepened at the same time (to 400–700 m). Such double-maxima vertical pattern was eventually disturbed by winter convection at the beginning of 2017, increasing salinities throughout the water column. A new episode of very strong inflow of high salinity waters from the Northern Ionian was observed in late winter and spring of 2017, this time restricted almost to the surface. As most of 2017 was characterized by extremely dry conditions, low riverine inputs and warmer than usual summer over the Adriatic and Northern Ionian, salinity values above the sharp and shallow (15–40 m) thermocline significantly increased. The maximum recorded salinity was 39.26, as measured by the Argo float in the Southern Adriatic. Surface salinity maximum events, but with much lower intensity, have been documented in the past. Both past events and the 2017 event were characterized by (i) concurrence with overall high salinity conditions and cyclonic or transitional phase of the Adriatic-Ionian Bimodal Oscillating System, (ii) very low river discharges preconditioning the events for a year or more, (iii) higher-than-average heat fluxes during most of the summer and early autumn periods, forming a stable warm layer above the thermocline, and (iv) higher-than-average E-P (evaporation minus precipitation) acting on this warm surface layer. Importantly, the 2017 event was also preceded by strong near-surface inflow of very saline waters from the Northern Ionian in early 2017.

Energy consumption prediction method based on LSSVM-PSO model for autonomous underwater gliders

Currently, most autonomous underwater gliders (AUGs) operate on primary lithium batteries. As the state of charge of a primary lithium battery and the influence of marine environment on the glider are difficult to measure, it is hard to forecast the energy consumption of a glider accurately, which has caused the failure of many glider missions. For the purpose of safely deploying the AUG mission and effectively optimizing the motion parameters to increase the endurance, it is very important to make an accurate energy consumption prediction model of the AUG. In this paper, a novel model based on the least squares support vector machine (LSSVM) and particle swarm optimization (PSO) algorithm, namely the LSSVM-PSO model, is proposed to forecast the energy consumption of the AUG. Considering that the kernel function and the LSSVM related parameters have a great influence on the performance of the prediction model, several LSSVM models based on different kernel functions for energy consumption prediction are established, and the parameters are optimized by the PSO algorithm. The performance of LSSVM-PSO models with different kernel functions are compared based on the sea trial data. The results indicate that the LSSVM-PSO model with a radial basis kernel function has a higher accuracy than other models for energy consumption prediction. Moreover, the performance of the LSSVM-PSO model trained by different sample sizes and that of the conventional mathematical energy consumption prediction model are compared. The results demonstrate that the LSSVM-PSO model is superior with a large enough training sample size.

Structure and Transport of Atlantic Water North of Svalbard From Observations in Summer and Fall 2018

AbstractThe transport of warm Atlantic Waters north of Svalbard is one of the major heat and salt sources to the Arctic Ocean. The circulation pathways and the associated heat transport influence the variability in the Arctic sea ice extent, the onset of freezing, and marine ecosystems. We present observations obtained from research cruises and an autonomous underwater glider mission in summer and fall 2018, to describe the hydrographic structure, volume transport, and circulation patterns of the warm Atlantic Water Boundary Current between 12°E and 24°E north of Svalbard. The Atlantic Water volume transport reaches a maximum of 3.0 ± 0.2 Sv in October, with an intraseasonal variability of 1 Sv (1 Sv = 106 m3 s−1). During summer and late fall, we observed an Atlantic Water recirculation flowing westward (0.1–0.2 Sv) in the outer part of the section away from the shelf break. This counter current appears to be a part of an anticyclonic circulation in the Sofia Deep. The strength of the Atlantic Water recirculation and the Atlantic Water boundary current is very sensitive to the wind stress curl: The boundary current volume transport doubled in less than a week, corresponding to a transition from strongly negative (−10−6 N m−3) to strongly positive (10−6 N m−3) wind stress curl over the Sofia Deep. A previously unknown, deep bottom‐intensified current is observed to flow parallel to the boundary current, between the 1,500 and 2,000 m isobaths. Historical data in the region support the presence of the bottom‐intensified current.

Breaking of Internal Waves and Turbulent Dissipation in an Anticyclonic Mode Water Eddy

AbstractA 4-month glider mission was analyzed to assess turbulent dissipation in an anticyclonic eddy at the western boundary of the subtropical North Atlantic. The eddy (radius ≈ 60 km) had a core of low potential vorticity between 100 and 450 m, with maximum radial velocities of 0.5 m s−1 and Rossby number ≈ −0.1. Turbulent dissipation was inferred from vertical water velocities derived from the glider flight model. Dissipation was suppressed in the eddy core (ε ≈ 5 × 10−10 W kg−1) and enhanced below it (>10−9 W kg−1). Elevated dissipation was coincident with quasiperiodic structures in the vertical velocity and pressure perturbations, suggesting internal waves as the drivers of dissipation. A heuristic ray-tracing approximation was used to investigate the wave–eddy interactions leading to turbulent dissipation. Ray-tracing simulations were consistent with two types of wave–eddy interactions that may induce dissipation: the trapping of near-inertial wave energy by the eddy’s relative vorticity, or the entry of an internal tide (generated at the nearby continental slope) to a critical layer in the eddy shear. The latter scenario suggests that the intense mesoscale field characterizing the western boundaries of ocean basins might act as a “leaky wall” controlling the propagation of internal tides into the basin’s interior.

Modeling for the performance of navigation, control and data post-processing of underwater gliders

Underwater gliders allow efficient monitoring in oceanography. In contrast to buoys, which log oceanographic data at individual depths at only one location, gliders can log data over a period of up to one year by following predetermined routes. In addition to the logged data from the available sensors, usually a conductivity-temperature-depth (CTD) sensor, the depth-average velocity can also be estimated using the horizontal glider velocity and the GPS update in a dead-reckoning algorithm. The horizontal velocity is also used for navigation or planning a long-term glider mission. This paper presents an investigation to determine the horizontal glider velocity as accurately as possible. For this, Slocum glider flight models used in practice will be presented and compared. A glider model for a steady-state gliding motion based on this analysis is described in detail. The approach for estimating the individual model parameters using nonlinear regression will be presented. In this context, a robust method to accurately detect the angle of attack is presented and the requirements of the logged vehicle data for statistically verified model parameters are discussed. The approaches are verified using logged data from glider missions in the Indian Ocean from 2016 to 2018. It is shown that a good match between the logged and the modeled data requires a time-varying model, where the model parameters change with respect to time. A reason for the changes is biofouling, where organisms settle and grow on the glider. The proposed method for deciphering an accurate horizontal glider velocity could serve to improve the dead-reckoning algorithm used by the glider for calculating depth-average velocity and for understanding its errors. The depth-average velocity is used to compare ocean current models from CMEMS and HYCOM with the glider logged data.