Using an eddy-tracking algorithm to understand the impact of assimilating altimetry data on the eddy characteristics of the Agulhas system

A complex and highly dynamical ocean region, the Agulhas Current System plays an important role in the transfer of energy, nutrients and organic material from the Indian to the Atlantic Ocean. Its dynamics are not only important locally, but affect the global ocean-atmosphere system. In working towards improved ocean reanalysis and forecasting capabilities, it is important that numerical models simulate mesoscale variability accurately—especially given the scarcity of coherent observational platforms in the region. Data assimilation makes use of scarce observations, a dynamical model and their respective error statistics to estimate a new, improved model state that minimises the distance to the observations whilst preserving dynamical consistency. Qualitatively, it is unclear whether this minimisation directly translates to an improved representation of mesoscale dynamics. In this study, the impact of assimilating along-track sea-level anomaly (SLA) data into a regional Hybrid Coordinate Ocean Model (HYCOM) is investigated with regard to the simulation of mesoscale eddy characteristics. We use an eddy-tracking algorithm and compare the derived eddy characteristics of an assimilated (ASSIM) and an unassimilated (FREE) simulation experiment in HYCOM with gridded satellite altimetry-derived SLA data. Using an eddy tracking algorithm, we are able to quantitatively evaluate whether assimilation updates the model state estimate such that simulated mesoscale eddy characteristics are improved. Additionally, the analysis revealed limitations in the dynamical model and the data assimilation scheme, as well as artefacts introduced from the eddy tracking scheme. With some exceptions, ASSIM yields improvements over FREE in eddy density distribution and dynamics. Notably, it was found that FREE significantly underestimates the number of eddies south of Madagascar compared to gridded altimetry, with only slight improvements introduced through assimilation, highlighting the models’ limitation in sustaining mesoscale activity in this region. Interestingly, it was found that the threshold for the maximum eddy propagation velocity in the eddy detection scheme is often exceeded when data assimilation relocates an eddy, causing the algorithm to interpret the discontinuity as eddy genesis, which directly influences the eddy count, lifetime and propagation velocity, and indirectly influences other metrics such as non-linearity. Finally, the analysis allowed us to separate eddy kinetic energy into contributions from detected mesoscale eddies and meandering currents, revealing that the assimilation of SLA has a greater impact on mesoscale eddies than on meandering currents.     

The emergence of equatorial deep jets in an idealised primitive equation model: an interpretation in terms of basin modes

Ocean circulation models do not generally exhibit equatorial deep jets (EDJs), even though EDJs are a recognised feature of the observed ocean circulation along the equator and they are thought to be important for tracer transport along the equator and even equatorial climate. EDJs are nevertheless found in nonlinear primitive equation models with idealised box geometry. Here we analyse several such model runs. We note that the variability of the zonal velocity in the model is dominated by the gravest linear equatorial basin mode for a wide range of baroclinic vertical normal modes and that the EDJs in the model are dominated by energy contained in vertical modes between 10 and 20. The emergence of the EDJs is shown to involve the linear superposition of several such neighbouring basin modes. Furthermore, the phase of these basin modes is set at the start of the model run and, in the case of the reference experiment, the same basin modes can be found in a companion experiment in which the amplitude of the forcing has been reduced by a factor of 1000. We also argue that following the spin-up, energy must be transferred between different vertical modes. This is because the model simulations are dominated by downward phase propagation following the spin-up whereas our reconstructions imply episodes of upward and downward propagation. The transfer of energy between the vertical modes is associated with a decadal modulation of the EDJs.     

Late Holocene mangrove dynamics dominated by autogenic processes

Generally, palaeoenvironmental interpretations consider only allogenic processes, when autogenic factors may have a strong influence on proxies of stratigraphic sequences. For instance, the Holocene history of the vegetation along the southern littoral of the State of Bahia in north‐eastern Brazil is characterized by mangrove dynamics controlled by allogenic processes. However, over smaller timescales (~700 years), autogenic processes may have controlled vegetation dynamics and hence observed pollen distribution. This work proposes tidal channel dynamics as one of the main cause for changes in pollen assemblage along the studied stratigraphic profiles during the last centuries, based on sedimentology, pollen and elemental analysis (δ¹³C, δ¹⁵N and C/N) and radiocarbon dating of sedimentary organic matter from two cores sampled from an abandoned meander and a tidal flat at the mouth of the Jucuruçu River. One core was sampled from a mangrove formed during the past ~550 cal yr bp . Another core recorded sediments in a várzea forest (swamp seasonally and permanently inundated by freshwater) located ~2.7 km from the current shoreline, which displayed a maximum age of ~680 cal yr bp . Two facies associations were identified: tidal channel (A) and tidal flat/oxbow lake (B). This work proposes allogenic processes as the main driving forces controlling the wetlands dynamics at the studied site during the Holocene. However, our data also reveal that part of the changes in vegetation over the last ~700 years reflect tidal channels and tidal flats development, which represent autogenic processes. The change in timescale analysis from the Holocene to recent centuries may have weakened the influence of allogenic factors. However, this needs interpretation with reference to the spatial scale of the depositional environment as the larger the depositional system analyzed, the stronger the influence of autogenic processes on stratigraphic sequences over longer timescales. Copyright © 2017 John Wiley & Sons, Ltd.     

Monitoring fluid substitution in rock samples from noise correlation

An alternative laboratory technique to measure the elastic constants of solid samples, based on the analysis of the cross‐correlation spectra of the vibratory response of randomly excited short solid cylinders, has been recently proposed. The aim of this paper is to check the ability of the technique called passive ultrasonic interferometry to monitor fluid substitution in different rock samples. Velocity variations due to fluid substitution are easily measured if the wave attenuation in the fluid‐saturated rock is not too large (typically in rocks with few cracks or microfractures). The experimental results are in agreement with the predictions of Biot–Gassmann poroelastic theory. The effect of substituting water with a stiffer saturating fluid, such as ethylene glycol, is to increase the overall bulk modulus of the rock, without any substantial effect on shear modulus. Furthermore, the experimental results compare well with those obtained independently with conventional pulse‐transmission technique using ultrasonic transducers. However, the measured pulse‐transmission bulk moduli are slightly larger than the corresponding measured ultrasonic interferometry moduli, with the deviation increasing with increasing fluid viscosity. This can be explained by dispersion due to wave‐induced flow of the viscous fluid since pulse‐transmission experiments involve higher frequencies than ultrasonic interferometry experiments.     

Quality Assessment of the French OpenStreetMap Dataset

The concept of Volunteered Geographic Information (VGI) has recently emerged from the new Web 2.0 technologies. The OpenStreetMap project is currently the most significant example of a system based on VGI. It aims at producing free vector geographic databases using contributions from Internet users. Spatial data quality becomes a key consideration in this context of freely downloadable geographic databases. This article studies the quality of French OpenStreetMap data. It extends the work of Haklay to France, provides a larger set of spatial data quality element assessments (i.e. geometric, attribute, semantic and temporal accuracy, logical consistency, completeness, lineage, and usage), and uses different methods of quality control. The outcome of the study raises questions such as the heterogeneity of processes, scales of production, and the compliance to standardized and accepted specifications. In order to improve data quality, a balance has to be struck between the contributors' freedom and their respect of specifications. The development of appropriate solutions to provide this balance is an important research issue in the domain of user‐generated content.     

A pilot study of genetic differentiation between two phenotypes of a Mediterranean population of the bivalve Cerastoderma glaucum and genetic discrimination with other Cerastoderma glaucum and Cerastoderma edule populations outside the Mediterranean

The internal transcribed spacer 1 (ITS1) region of 29 individuals of Cerastoderma glaucum (from the Mediterranean Sea, the Atlantic and the North Sea) and 18 individuals of Cerastoderma edule (from the Atlantic and the North Sea) and the cytochrome c oxidase subunit I (COI) region of 43 individuals of C. glaucum (from the Mediterranean Sea, the Atlantic and the North Sea) and 9 individuals of C. edule (from the Atlantic and the North Sea) were PCR amplified and sequenced. The ITS1 sequences led us to describe 27 genetic haplotypes, while 21 genetic haplotypes were determined via the COI sequences. The ITS1 and the COI sequences revealed an important genetic variability within the Mediterranean population of C. glaucum, which contained two different phenotypes: orange foot and yellow foot. A genetic differentiation between the two phenotypes was revealed by the nucleotide diversity index (π) and is strengthened by the AMOVA analysis. This result leads us to suspect the presence of two different groups in the same population of C. glaucum. Nevertheless to be confirmed this hypothesis requires further studies using more locations and a larger number of sample sizes.     

Ocean expansion: The role of detachment faults

Detachment faulting at slow spreading ocean ridge axes is recognized as a major surface creation mechanism, yet the structural relationships of these faults with feeder-dykes of on-axis volcanoes remained unresolved. This summary study shows that surface creation leading to ocean widening is exclusively controlled by detachment faults, shallow tracers of tectonic stresses induced by the westward drift of plates. Volcanoes are fed by feeder-dykes following on-axis rotational detachment faults. Once formed volcanoes are dragged along the detachment whose footwall is made of mantle material sometimes hosting gabbro sills. Due to the faster drift of the uppermost lithospheric layer, the feeder-dykes are then intersected by active deeper low-angle detachments, become inactive and are replaced by new ones on-axis. Rooted vertically on either side of the plate boundary, the detachment flexing is all the earlier and more progressive as the faults are far from the axis, positioning gabbro as sills at shallow level within a deformed mantle interspersed with cataclasite horizons. Correlations between shallow and deep lithospheric processes are then clarified.     

Acceleration of thermodynamic computations in fluid flow applications

Reservoir simulators model the highly nonlinear partial differential equations that represent flows in heterogeneous porous media. The system is made up of conservation equations for each thermodynamic species, flash equilibrium equations and some constraints. With advances in Field Development Planning (FDP) strategies, clients need to model highly complex Improved Oil Recovery processes such as gas re-injection and CO2 injection, which requires multi-component simulation models. The operating range of these simulation models is usually around the mixture critical point and this can be very difficult to simulate due to phase mislabeling and poor nonlinear convergence. We present a Machine Learning (ML) based approach that significantly accelerates such simulation models. One of the most important physical parameters required in order to simulate complex fluids in the subsurface is the critical temperature (T_crit). There are advanced iterative methods to compute the critical point such as the algorithm proposed by Heidemann and Khalil (AIChE J 26,769–799, 1980) but, because these methods are too expensive, they are usually replaced by cheaper and less accurate methods such as the Li-correlation (Reid and Sherwood 1966). In this work we use a ML workflow that is based on two interacting fully connected neural networks, one a classifier and the other a regressor, that are used to replace physical algorithms for single phase labelling and improve the convergence of the simulator. We generate real time compositional training data using a linear mixing rule between the injected and the in-situ fluid compositions that can exhibit temporal evolution. In many complicated scenarios, a physical critical temperature does not exist and the iterative sequence fails to converge. We train the classifier to identify, a-priori, if a sequence of iterations will diverge. The regressor is then trained to predict an accurate value of T_crit. A framework is developed inside the simulator based on TensorFlow that aids real time machine learning applications. The training data is generated within the simulator at the beginning of the simulation run and the ML models are trained on this data while the simulator is running. All the run-times presented in this paper include the time taken to generate the training data and train the models. Applying this ML workflow to real field gas re-injection cases suffering from severe convergence issues has resulted in a 10-fold reduction of the nonlinear iterations in the examples shown in this paper, with the overall run time reduced 2- to 10-fold, thus making complex FDP workflows several times faster. Such models are usually run many times in history matching and optimization workflows, which results in compounded computational savings. The workflow also results in more accurate prediction of the oil in place due to better single phase labelling.