Showing papers in "Ocean Dynamics in 2022"
TL;DR: In this paper , the authors investigated the role of physical drivers in post-2010 sargassum blooms in the Central West Atlantic (CWA), using ocean and atmospheric re-analyses and satellite-derived datasets.
Abstract: Abstract Since 2011, unprecedented pelagic sargassum seaweed blooms have occurred across the tropical North Atlantic, with severe socioeconomic impacts for coastal populations. To investigate the role of physical drivers in post-2010 sargassum blooms in the Central West Atlantic (CWA), conditions are examined across the wider tropical North Atlantic, using ocean and atmospheric re-analyses and satellite-derived datasets. Of particular consequence for the growth and drift of sargassum are patterns and seasonality of winds and currents. Results suggest that in years of exceptionally large sargassum blooms (2015, 2018), the Intertropical Convergence Zone (ITCZ), an area of maximum wind convergence where sargassum naturally accumulates, shifted southward, towards nutrient-rich waters of the Amazon River plume and the equatorial upwelling zone further stimulating sargassum growth. These changes are associated with modes of natural variability in the tropical Atlantic, notably a negative phase of the Atlantic Meridional Mode (AMM) in 2015 and 2018, and a positive phase of the Atlantic Niño in 2018. Negative AMM in these 2 years is also associated with stronger trade winds and enhanced northwest Africa upwelling, probably resulting in stronger southwestward nutrient transport into the eastern part of CWA. Moreover, in contrast with most years, important secondary winter blooms took place in both 2015 and 2018 in the northern part of CWA, associated with excessive wind-driven equatorial upwelling and anomalously strong northwestward nutrient transport.
14 citations
TL;DR: In this article , a super-resolution data assimilation (SRDA) method is proposed to improve the performance of a data-assimilation system by scaling up the model resolution.
Abstract: Abstract Increasing model resolution can improve the performance of a data assimilation system because it reduces model error, the system can more optimally use high-resolution observations, and with an ensemble data assimilation method the forecast error covariances are improved. However, increasing the resolution scales with a cubical increase of the computational costs. A method that can more effectively improve performance is introduced here. The novel approach called “Super-resolution data assimilation” (SRDA) is inspired from super-resolution image processing techniques and brought to the data assimilation context. Starting from a low-resolution forecast, a neural network (NN) emulates the fields to high-resolution, assimilates high-resolution observations, and scales it back up to the original resolution for running the next model step. The SRDA is tested with a quasi-geostrophic model in an idealized twin experiment for configurations where the model resolution is twice and four times lower than the reference solution from which pseudo-observations are extracted. The assimilation is performed with an Ensemble Kalman Filter. We show that SRDA outperforms both the low-resolution data assimilation approach and a version of SRDA with cubic spline interpolation instead of NN. The NN’s ability to anticipate the systematic differences between low- and high-resolution model dynamics explains the enhanced performance, in particular by correcting the difference of propagation speed of eddies. With a 25-member ensemble at low resolution, the SRDA computational overhead is 55% and the errors reduce by 40%, making the performance very close to that of the high-resolution system (52% of error reduction) that increases the cost by 800%. The reliability of the ensemble system is not degraded by SRDA.
5 citations
TL;DR: In this article , the spatial distribution and seasonal variability of mesoscale eddy observations derived from the AVISO eddy atlas were assessed in the Caribbean Sea during 1993-2019.
Abstract: Abstract The spatial distribution, and the monthly and seasonal variability of mesoscale eddy observations derived from the AVISO eddy atlas are assessed in the Caribbean Sea during 1993–2019. The average lifetime for the whole set of eddies is 62 ± 37 days, mean amplitude of 7 ± 4 cm for cyclonic and 7 ± 4 cm for anticyclonic and mean radius of 100 ± 31 km for cyclonic and 108 ± 32 km for anticyclonic. Cyclonic eddies are on average more nonlinear than anticyclonic ones. The spatio-temporal variability in the number of eddy observations is evaluated against the Mean Eddy Kinetic Energy (MEKE) derived from geostrophic currents as well as from seasonal winds. Spatial distribution of eddy observations is correlated with MEKE while the migration of the intertropical convergence zone explains the advection of eddies towards the southern part of the basin.
4 citations
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TL;DR: In this article , a coupled wave and ocean model is applied to the region of Galway Bay in the west of Ireland, using the numerical modelling suite COAWST, and the authors focus on the impact of the currents and sea level on the sea state during Storm Hector.
Abstract: A coupled wave and ocean model is applied to the region of Galway Bay in the west of Ireland, using the numerical modelling suite COAWST. The coupled model was validated in a previous study. Here we focus on the impact of the currents and sea level on the sea state during Storm Hector (2018/06/14). The purpose of the research is to improve the wave dynamics knowledge specifically in Galway Bay by highlighting and quantifying the dominant current-induced mechanisms on the sea state observed numerically. We want to know where wave-current interaction is modifying the sea state in the bay, and if the change is significant to justify the use of a coupled model for an operational application. We show that the impacts of the tidal sea surface height on bottom friction and of the current-induced refraction on the spatial distribution of the waves are the dominant mechanisms. Those two effects are well-documented and observed in the literature already. A strong feedback impact of the coupling is also put into evidence. The wave-induced response in terms of currents leads to a noticeable variation in terms of wave height. Less documented in the literature, we discuss the link between current-induced refraction and the reduction of wave generation by wind.
2 citations
TL;DR: In this article , a spatially and temporally comparative observational and model wave power results are provided, providing new information on the accuracy of model estimates, while showcasing in situ wave power trends at 29 sites around the U.S. coastline.
Abstract: Abstract Observational data are successfully assessed to investigate wave power (wave energy flux per unit of wave-crest) trends within four coastal regions around the US, a parameter that is deemed vital to those responsible for coastal protection and community resilience. This study tests for shifting observational inter-annual wave power trends using a newly developed, unique, United States Army Corps of Engineers Quality Controlled Consistent Measurement Archive, and offers a viable methodology to remove documented observational time series data discontinuations. This study is one of the first to show spatially and temporally comparative observational and model wave power results, providing new information on the accuracy of model wave power estimates, while showcasing in situ wave power trends at 29 sites around the U.S. coastline. Overall, the majority of the eastern Pacific Ocean and Hawaii wave power trends are downward, with mixed slope wave power trends apparent within the Atlantic Ocean and the Gulf of Mexico. Observational and model results are similar with respect to timing, but not magnitude, of wave power peaks in long-term inter-annual trends, with the moored buoy data presenting smaller wave power ranges for two (eastern Pacific Ocean and Hawaii) of the four regions. Additionally, the detection of a noticeable variability in the wave power trend direction within each region suggests that site-specific wave power trends should not be generalised to represent a large region. This work demonstrates that observational data are essential in local and regional wave climate studies to accurately estimate wave power for coastal planners and engineers.
2 citations
TL;DR: In this article , the bottom friction coefficient (BFC) can be related to the roughness of the sea bed, and sedimentological data can be beneficial in estimating BFCs.
Abstract: Abstract Accurately representing the bottom friction effect is a significant challenge in numerical tidal models. Bottom friction effects are commonly defined via parameter estimation techniques. However, the bottom friction coefficient (BFC) can be related to the roughness of the sea bed. Therefore, sedimentological data can be beneficial in estimating BFCs. Taking the Bristol Channel and Severn Estuary as a case study, we perform a number of BFC parameter estimation experiments, utilising sedimentological data in a variety of ways. Model performance is explored through the results of each parameter estimation experiment, including applications to tidal range and tidal stream resource assessment. We find that theoretically derived sediment-based BFCs are in most cases detrimental to model performance. However, good performance is obtained by retaining the spatial information provided by the sedimentological data in the formulation of the parameter estimation experiment; the spatially varying BFC can be represented as a piecewise-constant field following the spatial distribution of the observed sediment types. By solving the resulting low-dimensional parameter estimation problem, we obtain good model performance as measured against tide gauge data. This approach appears well suited to modelling tidal range energy resource, which is of particular interest in the case study region. However, the applicability of this approach for tidal stream resource assessment is limited, since modelled tidal currents exhibit a strong localised response to the BFC; the use of piecewise-constant (and therefore discontinuous) BFCs is found to be detrimental to model performance for tidal currents.
TL;DR: In this article , a native nested configuration of the ROMS model is implemented on the marine area between the Ligurian and Tyrrhenian basins, which includes the Tuscany Archipelago.
Abstract: Abstract A native nested configuration of the ROMS model is implemented on the marine area between the Ligurian and Tyrrhenian basins, which includes the Tuscany Archipelago. Initial and boundary conditions are provided by the CMEMS Mediterranean Sea Physical Reanalysis product (1/16°), feeding the parent ROMS model (BLUE, 1/72°), in which a high-resolution grid is nested (PURPLE, 1/216°). Atmospheric forcing comes from a downscaled version of ERA5 reanalysis. Temperature and salinity profiles from gliders and floats, and HF-radar-derived surface currents, are compared to model outputs within the high-resolution area for the whole year 2017. Results show the downscaling procedure is able to reduce model errors for temperature profiles, whereas errors in salinity profiles remain comparable. However, the downscaled model cannot recover large errors inherited from the parent one. The mean bias largest values found in both temperature and salinity profiles may be explained by a model underestimation of the depth of stable stratification limit with respect to field data. Errors in surface currents are reduced for the downscaled dynamics and appear to be uncorrelated to the original CMEMS product, being surface dynamics less affected by initial condition than by atmospheric forcing. A simple scalar metric, to quantify the error in the surface current vector fields from observations and models, is proposed. The novel metric allows to better quantify the improvement gained by the downscaling procedure.
TL;DR: In this article , the authors provide a brief description and assessment of the oceanic fields analyzed in the newly developed eddy-resolving quasi-global ocean reanalysis product, named the Japan Coastal Ocean Predictability Experiments-Forecasting Global Ocean (JCOPE-FGO).
Abstract: Abstract In the present research, we provide a brief description and assessment of the oceanic fields analyzed in the newly developed eddy-resolving quasi-global ocean reanalysis product, named the Japan Coastal Ocean Predictability Experiments-Forecasting Global Ocean (JCOPE-FGO). This product covers the quasi-global ocean with a horizontal resolution of 0.1° × 0.1°. Validations of analyzed temperature and salinity fields by JCOPE-FGO against in situ observations revealed that our product can capture various aspects of observed hydrographic structures in the world ocean, including frontal structures near the surface and thermohaline properties of water masses, as well as their spatiotemporal variability. Furthermore, we have assessed dynamical fields analyzed in JCOPE-FGO using satellite altimeters and surface drifters, and found that our product can represent the mean state and variability of the upper ocean circulation in many regions. A notable feature of JCOPE-FGO is the inclusion of an updated global river runoff, and impacts of river forcing have been assessed by an additional reanalysis experiment without river forcing. We found that the removal of continental river discharge leads to dramatic changes in the near-surface salinity and related fields around river mouths of large rivers, but large changes are mostly confined to narrow regions near the coast. As an example of the substantial impact of river runoff, we discuss the dispersion of low-salinity water from the Mississippi river to the Gulf of Mexico: a comparison between the analyzed salinity fields from both reanalysis products with those from satellite observations demonstrated that the inclusion of river runoff is essential for an accurate representation of its seasonal variability. Several key issues that warrant further improvements are discussed for future development.
TL;DR: In this paper , the authors analyzed the effect of these changes on tidal asymmetry, based on numerical modeling with high-resolution bathymetry data, and discussed possible adaptations of the import and export behavior in intertidal systems.
Abstract: Abstract The recent morphological development of the German Wadden Sea (North Sea, Europe) has been characterized by expanding intertidal flats and deepening, narrowing tidal channels at declining subtidal volume. This study analyzes the effect of these changes on tidal asymmetry, based on numerical modeling with high-resolution bathymetry data, and discusses possible adaptations of the import and export behavior in intertidal systems. As common descriptors of tidal asymmetry may show a high spatial variability in bathymetrically complex intertidal systems, we develop a novel subregion averaging approach for a more robust trend estimation. Our data reveal a statistically significant decrease in flood and flood current duration in the period from 1996 to 2016 resulting in declining flood dominance or enhanced ebb dominance in most tidal basins of the German Wadden Sea. Mean and peak current asymmetry also indicate significant decreases in mean flood current magnitude. We relate decreasing flood dominance mostly to local bathymetric volume changes rather than tidal amplitude. However, it appears likely that the sum of local effects facilitates the adaptation of regional tidal dynamics which affects especially the northern German Bight. This regional shift is explained by the deceleration of rising tides due to increased friction on laterally expanded intertidal flats and decreased subtidal channel volume. The decrease in flood or increase in ebb dominance, respectively, indicates that the recent trend of sediment accretion in Wadden Sea areas may cease soon.
TL;DR: In this paper , the authors evaluated the effect of free drift sea ice on the Spitzbergen Shelf region using a beacon dataset showing strong free drift subdaily sea ice oscillations and a physics based point ice model.
Abstract: Abstract One of the major challenges facing global hydrodynamic tidal models is the modelling of the interaction between sea ice and tides in high-latitude waters. Recent studies have shown strong seasonal correlation between sea ice and tides. Hence, it is important to accurately model the effect of sea ice in a tidal model. Presence of sea ice leads to a frictional dissipation of tides. Most models either completely ignore sea ice or partly include it by assuming a fixed sea ice cover (landfast ice). However, sea ice can also be drifting and the nature of dissipation between drifting sea ice and tides is partly unknown. We assess the dissipation of tides due to free drift sea ice. In the absence of wind, this is negligible in the deeper and open ocean. For the shallow water regions, however, this dissipation is unknown. Here, we evaluate this dissipation for the Spitzbergen Shelf region using a beacon dataset showing strong free drift subdaily sea ice oscillations and a physics based point ice model. Two analyses were done which compared the model and observed motion. The analyses showed that for winds speeds below 8m/s and with low subdaily signals, the subdaily free drift sea ice motion is strongly connected to the tides and that the frictional dissipation is low. In the context of global tide and storm surge models, the dissipation from free drift sea ice on tides should be evaluated based on the region (deep ocean or shallow water) and existing wind conditions. In the presence of strong winds the dissipation between free drift sea ice and air can be significant on a subdaily scale even if there are no subdaily signals in the wind itself.
TL;DR: In this paper , along-track sea level data from satellite altimetry were used to build a training dataset whose predictors are the neighboring observations, and the generated dataset is on average 10% more correlated to the tide gauge records than the commonly used product from Copernicus.
Abstract: The sea level observations from satellite altimetry are characterised by a sparse spatial and temporal coverage. For this reason, along-track data are routinely interpolated into daily grids. The latter are strongly smoothed in time and space and are generated using an optimal interpolation routine requiring several pre-processing steps and covariance characterisation. In this study, we assess the potential of Random Forest Regression to estimate daily sea level anomalies. Along-track sea level data from 2004 are used to build a training dataset whose predictors are the neighbouring observations. The validation is based on the comparison against daily averages from tide gauges. The generated dataset is on average 10% more correlated to the tide gauge records than the commonly used product from Copernicus. While the latter is more optimised for the detection of spatial mesoscales, we show how the methodology of this study has the potential to improve the characterisation of sea level variability.