Defining Southern Ocean fronts using unsupervised classification

Oceanographic fronts are transitions between thermohaline structures with different characteristics. Such transitions are ubiquitous, and their locations and properties affect how the ocean operates as part of the global climate system. In the Southern Ocean, fronts have classically been defined using a small number of continuous, circumpolar features in sea surface height or dynamic height. Modern observational and theoretical developments are challenging and expanding this traditional framework to accommodate a more complex view of fronts. Here, we present a complementary new approach for calculating fronts using an unsupervised classification method called Gaussian mixture modelling (GMM) and a novel inter-class parameter called the I-metric. The I-metric approach produces a probabilistic view of front location, emphasising the fact that the boundaries between water masses are not uniformly sharp across the entire Southern Ocean. The I-metric approach uses thermohaline information from a range of depth levels, making it more general than approaches that only use near-surface properties. We train the GMM using an observationally constrained state estimate in order to have more uniform spatial and temporal data coverage. The probabilistic boundaries defined by the I-metric roughly coincide with several classically defined fronts, offering a novel view of this structure. The I-metric fronts appear to be relatively sharp in the open ocean and somewhat diffuse near large topographic features, possibly highlighting the importance of topographically induced mixing. For comparison with a more localised method, we also use an edge detection approach for identifying fronts. We find a strong correlation between the edge field of the leading principal component and the zonal velocity; the edge detection method highlights the presence of jets, which are supported by thermal wind balance. This more localised method highlights the complex, multiscale structure of Southern Ocean fronts, complementing and contrasting with the more domain-wide view offered by the I-metric. The Sobel edge detection method may be useful for defining and tracking smaller-scale fronts and jets in model or reanalysis data. The I-metric approach may prove to be a useful method for inter-model comparison, as it uses the thermohaline structure of those models instead of tracking somewhat ad hoc values of sea surface height and/or dynamic height, which can vary considerably between models. In addition, the general I-metric approach allows front definitions to shift with changing temperature and salinity structures, which may be useful for characterising fronts in a changing climate.

Defining Southern Ocean fronts using unsupervised classification

Oceanographic fronts are transitions between thermohaline structures with different characteristics. Such transitions are ubiquitous, and their locations and properties affect how the ocean operates as part of the global climate system. In the Southern Ocean, fronts have classically been defined using a small number of continuous, circumpolar features in sea surface height or dynamic height. Modern observational and theoretical developments are challenging and expanding this traditional framework to accommodate a more complex view of fronts. Here we present a complementary new approach for calculating fronts using an unsupervised classification method called Gaussian mixture modelling and a novel inter-class parameter called the I-metric. The I-metric approach produces a probabilistic view of front location, emphasising the fact that the boundaries between water masses are not uniformly sharp across the entire Southern Ocean. The I-metric approach uses thermohaline information from a range of depth levels, making it more general than approaches that only use near-surface properties. We train the statistical model on data from an observationally-constrained state estimate for more uniform spatial and temporal coverage. The probabilistic boundaries appear to be relatively sharp in the open ocean and somewhat diffuse near large topographic features, possibly highlighting the importance of topographically-induced mixing. For comparison with a more localised method, we use edge detection in principal component space and correlate the edges with surface velocities. The I-metric approach may prove to be a useful method for inter-model comparison, as it uses the thermohaline structure of those models instead of tracking somewhat ad-hoc values of sea surface height and/or dynamic height, which can vary considerably between models. In addition, the general I-metric approach allows front definitions to shift with changing temperature and salinity structures, which may be useful for characterising fronts in a changing climate.

Analysis of the Dynamic Height Distribution at the Estuary of the Odra River Based on Gravimetric Measurements Acquired with the Use of a Light Survey Boat—A Case Study

This article presents possible applications of a dynamic gravity meter (MGS-6, Micro-g LaCoste) for determining the dynamic height along the Odra River, in northwest Poland. The gravity measurement campaign described in this article was conducted on a small, hybrid-powered survey vessel (overall length: 9.5 m). We discuss a method for processing the results of gravimetric measurements performed on a mobile platform affected by strong external disturbances. Because measurement noise in most cases consists of signals caused by non-ideal observation conditions, careful attempts were made to analyze and eliminate the noise. Two different data processing strategies were implemented, one for a 20 Hz gravity data stream and another for a 1 Hz data stream. A comparison of the achieved results is presented. A height reference level, consistent for the entire estuary, is critical for the construction of a safe waterway system, including 3D navigation with the dynamic estimation of under-keel clearance on the Odra and other Polish rivers. The campaign was conducted in an area where the accuracy of measurements (levelling and gravimetric) is of key importance for shipping safety. The shores in the presented area of interest are swampy, so watercraft-based measurements are preferred. The method described in the article can be successfully applied to measurements in all near-zero-depth areas.

Predictive models of the preferential distribution of demersal fish larvae in the southern part of the California Current

Habitat characterization provides predictive information about the distribution of species and is useful for as­sessing habitat quality and population stability. Larval abundance of six frequent and abundant demersal species and the relationship of each with the environment were analysed through generalized additive models to determine their preferential distribution and predictive response to the environmental variables in the southern part of the California Current (25-31°N) between two periods of data collection: 1997-2000 and 2006-2010. Essentially, the main associated variables governing the distribution patterns were related to common and oceanographic characteristics of the water column (temperature and salinity at 50 m depth, dynamic height and degree of water column stratification); however, the set of variables and their ranges are usually species-specific. Species of northern distribution, Sebastes sp. and Citharichtys stigmaeus, were recorded mainly in newly emerged, relatively unstratified waters characterized by a shallow mixed layer and low temperatures. Low dynamic height values were the most significant predictor of larval distribution for Merluccius productus. Citharichthys xanthostigma and Symphurus atricaudus were widespread, distributed across the study area mainly in autumn in unstratified or stratified waters and at a shallow mixed layer. Particularly C. Xanthostigma and S. Lucioceps were related to high dynamic height val­ues, likely influenced by a coastal flow towards the pole, as evidenced by counter-currents.

Arctic Ocean near-surface circulation: altimetry and in situ observations along the Transpolar Drift.

<p>Recent decades have seen a strong intensification of major circulation systems in the Arctic Ocean, namely the Beaufort Gyre and Transpolar Drift. Observing and studying seasonal, interannual and decadal variability of large-scale Arctic Ocean surface circulation is a key element to understand changes in climate-relevant export of both sea ice and fresh surface water from the Arctic. However, lack of in-situ ocean surface velocity observations have prevented further investigation until recently.</p><p>In the past decade, charts of the Arctic geostrophic surface flow field have been derived from new satellite altimetry missions over the ice-covered oceans, such as CryoSat-2, which was launched in 2010. The altimetric measurements allow the detection of leads and therefore to retrieve sea surface height (SSH) across the ice-covered Arctic Ocean. Aiming to characterize the seasonal to interannual variability of geostrophic surface currents in the Transpolar Drift, we use SSH observations from the Cryosat-2 mission between 2011 and 2018.</p><p>Here we present an evaluation of optimally interpolated altimetric SSH anomalies against in situ ocean observations of both bottom pressure and dynamic Height in Fram Strait and north of Arctic Cape, in the years between 2016 and 2018. Following the assessment of the quality of altimetry-based SSH, we discuss the timescales of SSH variability in seasonally ice-covered regions. Moreover, from the comparison with ocean bottom pressure and dynamic height we will attribute the relative importance of mass and steric contributions to the variability of SSH along the two transects. From first preliminary results in a test year (2011), SSH at a meridional transect in central Fram Strait between 78°N and 80°N shows a seasonal cycle with minimum in the months of March and April, enhanced at the most southern mooring. </p>