Particle fluxes in the deep Eastern Mediterranean basins: the role of ocean vertical velocities

This paper analyzes the relationship between deep sedimentary fluxes and ocean current vertical velocities in an offshore area of the Ionian Sea, the deepest basin of the Eastern Mediterranean Sea. Sediment trap data are collected at 500 m and 2800 m depth in two successive moorings covering the period September 1999–May 2001. A tight coupling is observed between the upper and deep traps and the estimated particle sinking rates are more than 200 m day−1. The current vertical velocity field is computed from a 1/16°×1/16° Ocean General Circulation Model simulation and from the wind stress curl. Current vertical velocities are larger and more variable than Ekman vertical velocities, yet the general patterns are alike. Current vertical velocities are generally smaller than 1 m day−1: we therefore exclude a direct effect of downward velocities in determining high sedimentation rates. However we find that upward velocities in the subsurface layers of the water column are positively correlated with deep particle fluxes. We thus hypothesize that upwelling would produce an increase in upper ocean nutrient levels – thus stimulating primary production and grazing – a few weeks before an enhanced vertical flux is found in the sediment traps. High particle sedimentation rates may be attained by means of rapidly sinking fecal pellets produced by gelatinous macro-zooplankton. Other sedimentation mechanisms, such as dust deposition, are also considered in explaining large pulses of deep particle fluxes. The fast sinking rates estimated in this study might be an evidence of the efficiency of the biological pump in sequestering organic carbon from the surface layers of the deep Eastern Mediterranean basins

Particle fluxes in the deep Eastern Mediterranean basins: the role of ocean vertical velocities

This paper analyzes the relationship between deep sedimentary fluxes and ocean current vertical velocities in an offshore area of the Ionian Sea, the deepest basin of the Eastern Mediterranean Sea. Sediment trap data are collected at 500m and 2800m depth in two successive moorings covering the period September 1999–May 2001. A tight coupling is observed between the upper and deep traps and the estimated particle sinking rates are more than 200mday−1. The current vertical velocity field is computed from a 1/16 ×1/16 Ocean General Circulation Model simulation and from the wind stress curl. Current vertical velocities are larger and more variable than Ekman vertical velocities, yet the general patterns are alike. Current vertical velocities are generally smaller than 1mday−1: we therefore exclude a direct effect of downward velocities in determining high sedimentation rates. However we find that upward velocities in the subsurface layers of the water column are positively correlated with deep particle fluxes. We thus hypothesize that upwelling would produce an increase in upper ocean nutrient levels – thus stimulating primary production and grazing – a few weeks before an enhanced vertical flux is found in the sediment traps. High particle sedimentation rates may be attained by means of rapidly sinking fecal pellets produced by gelatinous macro-zooplankton. Other sedimentation mechanisms, such as dust deposition, are also considered in explaining large pulses of deep particle fluxes. The fast sinking rates estimated in this study might be an evi- Correspondence to: L. Patara ([email protected]) dence of the efficiency of the biological pump in sequestering organic carbon from the surface layers of the deep Eastern Mediterranean basins

Particle fluxes in the deep Eastern Mediterranean basins: the role of ocean vertical velocities

This paper analyzes the relationship between deep sedimentary fluxes and ocean current vertical velocities in an offshore area of the Ionian Sea, the deepest basin of the Eastern Mediterranean Sea. Sediment trap data are collected at 500 m and 2800 m depth in two successive moorings covering the period September 1999 – May 2001. A tight coupling is observed between the upper and deep traps and the deduced particle settling rates are larger than 200 m/day. The current vertical velocity field is computed from a high resolution Ocean General Circulation Model (OGCM) simulation and from the wind stress curl. Values are generally smaller than 1 m/day: we therefore exclude a direct effect of downward vertical velocities in determining sedimentation rates. However we find that upward vertical velocities in the subsurface layers of the water column are significantly correlated with deep particle fluxes. We thus hypothesize that upwelling would produce an increase in upper ocean nutrient levels - thus stimulating primary productivity and grazing - a few weeks before an enhanced vertical flux is found in the sediment traps. The role of ocean vertical velocities on deep particle fluxes would therefore be indirect. High particle sedimentation rates may be attained by means of rapidly sinking fecal pellets produced by gelatinous macro-zooplankton organisms. Other sedimentation mechanisms, such as dust deposition, are also taken into account in explaining large pulses of deep particle fluxes

The impact of a new high-resolution ocean model on the Met Office North-West European Shelf forecasting system

The North-West European Shelf ocean forecasting system has been providing oceanographic products for the European continental shelf seas for more than 15 years. In that time, several different configurations have been implemented, updating the model and the data assimilation components. The latest configuration to be put in operation, an eddy-resolving model at 1.5 km (AMM15), replaces the 7 km model (AMM7) that has been used for 8 years to deliver forecast products to the Copernicus Marine Environment Monitoring Service and its precursor projects. This has improved the ability to resolve the mesoscale variability in this area. An overview of this new system and its initial validation is provided in this paper, highlighting the differences with the previous version. Validation of the model with data assimilation is based on the results of 2 years (2016–2017) of trial experiments run with the low- and high-resolution systems in their operational configuration. The 1.5 km system has been validated against observations and the low-resolution system, trying to understand the impact of the high resolution on the quality of the products delivered to the users. Although the number of observations is a limiting factor, especially for the assessment of model variables like currents and salinity, the new system has been proven to be an improvement in resolving fine-scale structures and variability and provides more accurate information on the major physical variables, like temperature, salinity, and horizontal currents. AMM15 improvements are evident from the validation against high-resolution observations, available in some selected areas of the model domain. However, validation at the basin scale and using daily means penalized the high-resolution system and does not reflect its superior performance. This increment in resolution also improves the capabilities to provide marine information closer to the coast even if the coastal processes are not fully resolved by the model

A relocatable ocean model in support of environmental emergencies

During the Costa Concordia emergency case, regional, subregional, and relocatable ocean models have been used together with the oil spill model, MEDSLIK-II, to provide ocean currents forecasts, possible oil spill scenarios, and drifters trajectories simulations. The models results together with the evaluation of their performances are presented in this paper. In particular, we focused this work on the implementation of the Interactive Relocatable Nested Ocean Model (IRENOM), based on the Harvard Ocean Prediction System (HOPS), for the Costa Concordia emergency and on its validation using drifters released in the area of the accident. It is shown that thanks to the capability of improving easily and quickly its configuration, the IRENOM results are of greater accuracy than the results achieved using regional or subregional model products. The model topography, and to the initialization procedures, and the horizontal resolution are the key model settings to be configured. Furthermore, the IRENOM currents and the MEDSLIK-II simulated trajectories showed to be sensitive to the spatial resolution of the meteorological fields used, providing higher prediction skills with higher resolution wind forcing.MEDESS4MS Project; TESSA Project; MyOcean2 Projectinfo:eu-repo/semantics/publishedVersio

The impact of ocean‐wave coupling on the upper ocean circulation during storm events

Many human activities rely on accurate knowledge of the sea surface dynamics. This is especially true during storm events, when wave-current interactions might represent a leading order process of the upper ocean. In this study, we assess and analyze the impact of including three wave-dependent processes in the ocean momentum equation of the Met Office North West European Shelf ocean-wave forecasting system on the accuracy of the simulated surface circulation. The analysis is conducted using ocean currents and Stokes drift data produced by different implementations of the coupled forecasting systems to simulate the trajectories of surface (iSphere) and 15 m drogued (SVP) drifters affected by four storms selected from winter 2016. Ocean and wave simulations differ only in the degree of coupling and the skills of the Lagrangian simulations are evaluated by comparing model results against the observed drifter tracks. Results show that, during extreme events, ocean-wave coupling improves the accuracy of the surface dynamics by 4%. Improvements are larger for ocean currents on the shelf (8%) than in the open ocean (4%): this is thought to be due to the synergy between strong tidal currents and more mature decaying waves. We found that the Coriolis-Stokes forcing is the dominant wave-current interaction for both type of drifters; for iSpheres the secondary wave effect is the wave-dependent sea surface roughness while for SVPs the wave-modulated water-side stress is more important. Our results indicate that coupled ocean-wave systems may play a key role for improving the accuracy of particle transport simulations

Can wave coupling improve operational regional ocean forecasts for the north-west European Shelf?

Operational ocean forecasts are typically produced by modelling systems run using a forced mode approach. The evolution of the ocean state is not directly influenced by surface waves, and the ocean dynamics are driven by an external source of meteorological data which are independent of the ocean state. Model coupling provides one approach to increase the extent to which ocean forecast systems can represent the interactions and feedbacks between ocean, waves, and the atmosphere seen in nature. This paper demonstrates the impact of improving how the effect of waves on the momentum exchange across the ocean–atmosphere interface is represented through ocean–wave coupling on the performance of an operational regional ocean prediction system. This study focuses on the eddy-resolving (1.5 km resolution) Atlantic Margin Model (AMM15) ocean model configuration for the north-west European Shelf (NWS) region. A series of 2-year duration forecast trials of the Copernicus Marine Environment Monitoring Service (CMEMS) north-west European Shelf regional ocean prediction system are analysed. The impact of including ocean–wave feedbacks via dynamic coupling on the simulated ocean is discussed. The main interactions included are the modification of surface stress by wave growth and dissipation, Stokes–Coriolis forcing, and wave-height-dependent ocean surface roughness. Given the relevance to operational forecasting, trials with and without ocean data assimilation are considered. Summary forecast metrics demonstrate that the ocean–wave coupled system is a viable evolution for future operational implementation. When results are considered in more depth, wave coupling was found to result in an annual cycle of relatively warmer winter and cooler summer sea surface temperatures for seasonally stratified regions of the NWS. This is driven by enhanced mixing due to waves, and a deepening of the ocean mixed layer during summer. The impact of wave coupling is shown to be reduced within the mixed layer with assimilation of ocean observations. Evaluation of salinity and ocean currents against profile measurements in the German Bight demonstrates improved simulation with wave coupling relative to control simulations. Further, evidence is provided of improvement to simulation of extremes of sea surface height anomalies relative to coastal tide gauges

A study of CP violation in the decays B±→[K+K-π+π-]Dh± (h= K, π) and B±→[π+π-π+π-]Dh±

The first study of CP violation in the decay mode B±→[K+K-π+π-]Dh± , with h= K, π , is presented, exploiting a data sample of proton–proton collisions collected by the LHCb experiment that corresponds to an integrated luminosity of 9 \,fb - 1 . The analysis is performed in bins of phase space, which are optimised for sensitivity to local CP asymmetries. CP -violating observables that are sensitive to the angle γ of the Unitarity Triangle are determined. The analysis requires external information on charm-decay parameters, which are currently taken from an amplitude analysis of LHCb data, but can be updated in the future when direct measurements become available. Measurements are also performed of phase-space integrated observables for B±→[K+K-π+π-]Dh± and B±→[π+π-π+π-]Dh± decays

Measurement of τL using the Bs0 →J/ψη decay mode

Using a proton–proton collision data sample collected by the LHCb detector and corresponding to an integrated luminosity of 5.7fb-1 , the lifetime of the light Bs0 mass eigenstate, τL , is measured using the Bs0→J/ψη decay mode to be τL=1.445±0.016(stat)±0.008(syst)ps. A combination of this result with a previous LHCb analysis using an independent dataset corresponding to 3 fb - 1 of integrated luminosity gives τL=1.452±0.014±0.007±0.002ps, where the first uncertainty is statistical, the second due to the uncorrelated part of the systematic uncertainty and the third due to the correlated part of the systematic uncertainty