Earth observation and machine learning reveal the dynamics of productive upwelling regimes on the Agulhas Bank

The combined application of machine learning and satellite observations offers a new way for analysing complex ocean biological and physical processes. Here, an unsupervised machine learning approach, Self Organizing Maps (SOM), is applied to discover links between surface current variability and phytoplankton productivity during seasonal upwelling over the Agulhas Bank (South Africa), from 23 years (November-March 1997-2020) of daily satellite observations (surface current, sea surface temperature, chlorophyll-a). The SOM patterns extracted over this dynamically complex region, which is dominated by the Agulhas Current (AC), revealed 4 topologies/modes of the AC system. An AC flowing southwestward along the shelf edge is the dominant mode. An AC with a cyclonic meander near shelf is the second most frequent mode. An AC with a cyclonic meander off shelf and AC early retroflection modes are the least frequent. These AC topologies influence the circulation and the phytoplankton productivity on the shelf. Strong (weak) seasonal upwelling is seen in the AC early retroflection, the AC with a cyclonic meander near shelf modes and in part of the AC along the shelf edge mode (the AC with a cyclonic meander off shelf mode and in part the AC along the shelf edge mode). The more productive patterns are generally associated with a strong southwestward flow over the central bank caused by the AC intrusion to the east Bank or via an anticyclonic meander. The less productive situations can be related to a weaker southwest flow over the central bank, strong northeast flow on the eastern bank, and/or to a stronger northwest flow on the central bank. The SOM patterns show marked year-to-year variability. The high/low productivity events seem to be linked to the occurrence of extreme phases in climate variability modes (El Niño Southern Oscillation, Indian Ocean Dipole)

Platform effects on optical variability and prediction of underwater visibility

We present hydrographic and optical data collected concurrently from two different platforms, the R/P FLoating Instrument Platform and the R/V Kilo Moana, located about 2km apart in the Santa Barbara Channel in California. We show that optical variability between the two platforms was due primarily to platform effects, specifically the breakdown of stratification from mixing by the hull of R/P FLIP. Modeled underwater radiance distribution differed by as much as 50% between the two platforms during stratified conditions. We determine that the observed optical variability resulted in up to 57% differences in predicted horizontal visibility of a black target

Variability of mackerel fish catch and remotely-sensed biophysical controls in the eastern pemba channel

Advances in satellite remote sensing of environmental perturbations have become important in understanding variations of ocean productivity and small pelagic fish catches. This marine resource is vital for coastal populations dependent on artisanal fishing for their income and food security, such as in coastal East Africa. In this region, the eastern Pemba Channel (Tanzania) represents a hotspot area, for a variety of marine species including small pelagics and coral reef associated species. This study examines the links between mackerel fish catch, one of the important small pelagic fish for direct consumption in the region, and changes in environmental oceanographic parameters over the period 2012–2018. The fisheries catch data is a rare local dataset, consisting of daily mackerel landings (from 2012 onwards) and supplemented by qualitative information on the mackerel fishery obtained through interviews with local stakeholders. The physical factors influencing phytoplankton biomass, and in turn, mackerel fisheries yield is investigated, using remotely-sensed chlorophyll-a (Chl-a) and Sea Surface Temperature (SST), together with Mixed Layer Depth (MLD) data from the high-resolution ocean model NEMO. We show that seasonal variations in mackerel landings are positively (negatively) correlated with Chl-a (SST) with a 1-month time lag (i.e., biophysical factors change first, mackerel stocks follow one month later). On the eastern side of the Pemba Channel, cooler SST and higher Chl-a are observed during the Southeast monsoon accompanied by increased mackerel landings, suggestive of enhanced productivity. Interannually, these relationships remain valid both for monthly and annual means, which confirms the close link between the variations of mackerel and biophysical conditions. Analysis of the Chl-a and MLD anomalies, relative to the mean, reveals that the phytoplankton blooms observed on the eastern side of the Pemba Channel, during the Southeast monsoon, are likely due to the deepening of the mixed layer, which tends to entrain cold and nutrient rich waters from greater depths to the surface. We conclude that upper ocean mixing contributes to the observed enhanced productivity along with other environmental factors. Additionally, we show how our results can be applied in the management of the mackerel resource in the Pemba Channel

Productivity driven by Tana river discharge is spatially limited in Kenyan coastal waters

The Tana River is the longest river system in Kenya (~1000 km) and contributes ~ 50% of the total river discharge to Kenyan coastal waters. The river discharges significant amounts of nutrients and sediments, reaching ~24,000 tons per day during the rainy season (March–April), into Ungwana Bay (North Kenya Banks). The bay is an important habitat for high-value Panaeid prawn species which sustain important small-scale fisheries, semi-industrial bottom trawl prawn fisheries, and is the livelihood mainstay in the surrounding counties. In this study we analysed >20 years of satellite-derived chlorophyll-a observations (Chl-a, an index of phytoplankton biomass), along with in situ river discharge and rainfall data, to investigate if the Tana River discharge is a major driver of local phytoplankton biomass in Ungwana Bay and for the neighbouring Kenyan shelf. We find that during the rainy inter-monsoon (March–April), a significant positive relationship (r = 0.63, p < 0.0001) exists between river discharge and phytoplankton biomass. There is a clear time-lag between rainfall, river discharge (1-month lag) and local chlorophyll biomass (2-months lag after discharge). Unlike offshore waters which exhibit bi-annual chl-a peaks (0.22 mg m−3 in February, and 0.223 mg m−3 in August/September), Ungwana Bay displays a single peak per annum in July (2.51 mg m−3), with indications that river discharge sustains phytoplankton biomass for several months. Satellite-derived observations and Lagrangian tracking simulations indicate that higher Chl-a concentrations remain locally within the bay, rather than influencing the broader open waters of the North Kenya Banks that are mainly impacted by the wider oceanic circulation

A Major Ecosystem Shift in Coastal East African Waters During the 1997/98 Super El Niño as Detected Using Remote Sensing Data

Under the impact of natural and anthropogenic climate variability, upwelling systems are known to change their properties leading to associated regime shifts in marine ecosystems. These often impact commercial fisheries and societies dependent on them. In a region where in situ hydrographic and biological marine data are scarce, this study uses a combination of remote sensing and ocean modelling to show how a stable seasonal upwelling off the Kenyan coast shifted into the territorial waters of neighboring Tanzania under the influence of the unique 1997/98 El Niño and positive Indian Ocean Dipole event. The formation of an anticyclonic gyre adjacent to the Kenyan/Tanzanian coast led to a reorganization of the surface currents and caused the southward migration of the Somali–Zanzibar confluence zone and is attributed to anomalous wind stress curl over the central Indian Ocean. This caused the lowest observed chlorophyll-a over the North Kenya banks (Kenya), while it reached its historical maximum off Dar Es Salaam (Tanzanian waters). We demonstrate that this situation is specific to the 1997/98 El Niño when compared with other the super El-Niño events of 1972,73, 1982–83 and 2015–16. Despite the lack of available fishery data in the region, the local ecosystem changes that the shift of this upwelling may have caused are discussed based on the literature. The likely negative impacts on local fish stocks in Kenya, affecting fishers’ livelihoods and food security, and the temporary increase in pelagic fishery species’ productivity in Tanzania are highlighted. Finally, we discuss how satellite observations may assist fisheries management bodies to anticipate low productivity periods, and mitigate their potentially negative economic impacts

Lagrangian ocean analysis: fundamentals and practices

Lagrangian analysis is a powerful way to analyse the output of ocean circulation models and other ocean velocity data such as from altimetry. In the Lagrangian approach, large sets of virtual particles are integrated within the three-dimensional, time-evolving velocity fields. Over several decades, a variety of tools and methods for this purpose have emerged. Here, we review the state of the art in the field of Lagrangian analysis of ocean velocity data, starting from a fundamental kinematic framework and with a focus on large-scale open ocean applications. Beyond the use of explicit velocity fields, we consider the influence of unresolved physics and dynamics on particle trajectories. We comprehensively list and discuss the tools currently available for tracking virtual particles. We then showcase some of the innovative applications of trajectory data, and conclude with some open questions and an outlook. The overall goal of this review paper is to reconcile some of the different techniques and methods in Lagrangian ocean analysis, while recognising the rich diversity of codes that have and continue to emerge, and the challenges of the coming age of petascale computing

In-situ estimate of submesoscale horizontal eddy diffusion coefficients across a front

International audienceFronts, jets and eddies are ubiquitous features of the world oceans, and play a key role in regulating energy budget, heat transfer, horizontal and vertical transport, and biogeochemical processes. Although recent advances in computational power have favored the analysis of mesoscale and submesoscale dynamics from high-resolution numerical simulations, studies from in-situ observations are still relatively scarce. The small dimensions and short duration of such structures still pose major challenges for fine-scale dedicated field experiments. As a consequence, in-situ quantitative estimates of key physical parameters for high-resolution numerical models, such as horizontal eddy diffusion coefficients, are still lacking. The Latex10 campaign (September 1-24, 2010), within the LAgrangian Transport EXperiment (LATEX), adopted an adaptive sampling strategy that included satellite data, ship-based current measurements, and iterative Lagrangian drifter releases to successfully map coherent transport structures in the western Gulf of Lion. Comparisons with AVHRR imagery evidenced that the detected structures were associated with an intense frontal feature, originated by the convergence and subsequent stirring of colder coastal waters with warmer open-sea waters. We present a method for computing horizontal eddy diffusion coefficients by combining the stirring rates estimated from the Lagrangian drifter trajectories with the shapes of the surface temperature and salinity gradient (assumed to be at the equilibrium) from the ship thermosalinograph. The average value we obtained from various sections across the front is 2.5 m2 s-1, with horizontal scales (width of the front) ranging between 0.5 and 2.5 km. This is in line with the values commonly used for high-resolution numerical simulations. Further field experiment will be required to extend the results to different ocean regions and regimes, and to thoroughly test the robustness of the equilibrium hypothesis. Remote sensed measurements of sea surface temperature and elevation could also be used to compute fine-scale horizontal eddy diffusion coefficients over larger areas and for different ocean regions. However, the coarse resolution of current sea surface topography observations, and their unreliability over coastal regions, represent important limitations for this type of application. The velocity fields provided by the SWOT mission will allow to retrieve accurate high-resolution stirring rates across the ocean. Combining these rates with remote-sensed SST gradients will make possible to extend our analysis and investigate patterns and variability of submesoscale horizontal eddy diffusion at the global scale

Multi-platform synergy for the direct investigation of ocean fronts: a case study in the North-Western Mediterranean

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In situ estimates of submesoscale horizontal eddy diffusivity across an ocean front

International audienceIn the last decade, the rapid advancements in computational power have favored the development of high-resolution numerical models capable of directly resolving small-scale structures such as fronts and filaments. Such models have greatly improved our understanding of submesoscale dynamics. At the same time, the small dimensions and short duration of these structures still pose major challenges for small-scale dedicated field experiments. For this reason, submesoscale studies from in situ observations are still relatively scarce and quantitative estimates of key physical parameters for high-resolution numerical models, such as horizontal eddy diffusivity, are still lacking. This study presents a novel approach for computing in situ horizontal eddy diffusivity associated with frontal structures by combining cross-front widths derived from surface thermosalinograph sections with stirring rates estimated from Lagrangian drifter trajectories. The method is applied to the measurements collected across a frontal structure observed in the western part of the Gulf of Lion during the Latex10 campaign (LAgrangian Transport EXperiment, 1-24 September 2010). A total of 76 estimates of eddy diffusivity were obtained for strain rates of 0.70 and 1.21 day−1 and front widths (horizontal scales) ranging between 1 and 4 km. The estimates are log-normally distributed, with 70% of the values ranging between 0.4 and 5 m2 s−1. Further analysis based on high-resolution simulations and remote sensed observations, as well as dedicated field experiments will help to assess the robustness of some of the assumptions at the base of the proposed approach, and to extend the results to different ocean regions