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Abstract. Land-based coastal high-frequency (HF) radar systems provide operational measurements of coastal surface currents (within 1–3 m depth) with high spatial (300 m–10 km) and temporal (≤1 h) sampling resolutions, while the near-continuous altimetry missions provide information, from 1993 until today, on geostrophic currents in the global ocean with typical along-track and temporal sampling resolutions of >7 km and >9 days, respectively. During the last years, the altimetry community has made a step forward in improving these data in the coastal area, where the data present lower quality than in the open ocean. The combination of HF radar and altimetry measurements arises as a promising strategy to improve the continuous monitoring of the coastal area (e.g. by expanding the measurements made by HF radars to adjacent areas covered by the altimetry or by validating/confirming improvements brought by specific coastal algorithms or new altimeter missions). A first step towards this combination is the comparison of both data sets in overlapping areas. In this study, a HF radar system and two Jason-2 satellite altimetry products with different processing are compared over the period from 1 January 2009 to 24 July 2015. The results provide an evaluation of the performance of different coastal altimetry data sets within the study area and a better understanding of the ocean variability contained in the HF radar and altimetry data sets. Both observing systems detect the main mesoscale processes within the study area (the Iberian Poleward Current and mesoscale eddies), and the highest correlations between radar and altimetry (up to 0.64) occur in the slope where the Iberian Poleward Current represents a significant part of the variability in the circulation. Besides, the use of an Ekman model, to add the wind-induced current component to the altimetry-derived geostrophic currents, increases the agreement between both data sets (increasing the correlation by around 10 %).
Satellite altimeters provide continuous information of the sea level variability and mesoscale processes for the global ocean. For estimating the sea level above the geoid and monitoring the full ocean dynamics from altimeters measurements, a key reference surface is needed: The Mean Dynamic Topography (MDT). However, in coastal areas, where, in situ measurements are sparse and the typical scales of the motion are generally smaller than in the deep ocean, the global MDT solutions are less accurate than in the open ocean, even if significant improvement has been done in the past years. An opportunity to fill in this gap has arisen with the growing availability of long time-series of high-resolution HF radar surface velocity measurements in some areas, such as the south-eastern Bay of Biscay. The prerequisite for the computation of a coastal MDT, using the newly available data of surface velocities, was to obtain a robust methodology to remove the ageostrophic signal from the HF radar measurements, in coherence with the scales resolved by the altimetry. To that end, we first filtered out the tidal and inertial motions, and then, we developed and tested a method that removed the Ekman component and the remaining divergent part of the flow. A regional high-resolution hindcast simulation was used to assess the method. Then, the processed HF radar geostrophic velocities were used in synergy with additional in situ data, altimetry, and gravimetry to compute a new coastal MDT, which shows significant improvement compared with the global MDT. This study showcases the benefit of combining satellite data with continuous, high-frequency, and synoptic in situ velocity data from coastal radar measurements; taking advantage of the different scales resolved by each of the measuring systems. The integrated analysis of in situ observations, satellite data, and numerical simulations has provided a further step in the understanding of the local ocean processes, and the new MDT a basis for more reliable monitoring of the study area. Recommendations for the replicability of the methodology in other coastal areas are also provided. Finally, the methods developed in this study and the more accurate regional MDT could benefit present and future high-resolution altimetric missions.
Coastal mesoscale eddies are important oceanic structures partially responsible for regulating ocean-shelf exchanges. However, their description and characterization are challenging; observations are often too scarce for studying their physical properties and environmental impacts at the required spatio-temporal resolution. Therefore, models and data extrapolation methods are key tools for this purpose. Observations from high-frequency radar, one satellite and two gliders, are used here to better characterize the three-dimensional structure of a coastal mode-water eddy from a multiplatform approach in the southeastern Bay of Biscay in spring 2018. After the joint analysis of the observations, a three-dimensional data reconstruction method is applied to reconstruct the eddy current velocity field and estimate the associated water volume transport. The target eddy is detected by surface observations (high-frequency radar and satellite) for two weeks and presents similar dimensions and lifetimes as other eddies studied previously in the same location. However, this is the first time that the water column properties are also observed for this region, which depicts a mode-water eddy behavior, i.e., an uplift of the isopycnals in the near-surface and a downlift deeper in the water column. The reconstructed upper water column (1–100 m) eddy dynamics agree with the geostrophic dynamics observed by one of the gliders and result in cross-shelf inshore (offshore) volume transports between 0.04 (−0.01) and 0.15 (−0.11) Sv. The multiplatform data approach and the data reconstruction method are here highlighted as useful tools to characterize and three-dimensionally reconstruct coastal mesoscale processes in coastal areas.
Abstract. Submesoscale processes have a determinant role in the dynamics of oceans by transporting momentum, heat, mass, and particles. Furthermore, they can define niches where different phytoplankton species flourish and accumulate not only by nutrient provisioning but also by modifying the water column structure or active gathering through advection. In coastal areas, however, submesoscale oceanic processes act together with coastal ones, and their effect on phytoplankton distribution is not straightforward. The present study brings the relevance of hydrodynamic variables, such as vorticity, into consideration in the study of phytoplankton distribution, via the analysis of in situ and remote multidisciplinary data. In situ data were obtained during the ETOILE oceanographic cruise, which surveyed the Capbreton Canyon area in the southeastern part of the Bay of Biscay in early August 2017. The main objective of this cruise was to describe the link between the occurrence and distribution of phytoplankton spectral groups and mesoscale to submesoscale ocean processes. In situ discrete hydrographic measurements and multi-spectral chlorophyll a (chl a) fluorescence profiles were obtained in selected stations, while temperature, conductivity, and in vivo chl a fluorescence were also continuously recorded at the surface. On top of these data, remote sensing data available for this area, such as high-frequency radar and satellite data, were also processed and analysed. From the joint analysis of these observations, we discuss the relative importance and effects of several environmental factors on phytoplankton spectral group distribution above and below the pycnocline and at the deep chlorophyll maximum (DCM) by performing a set of generalized additive models (GAMs). Overall, salinity is the most important parameter modulating not only total chl a but also the contribution of the two dominant spectral groups of phytoplankton, brown and green algae groups. However, at the DCM, among the measured variables, vorticity is the main modulating environmental factor for phytoplankton distribution and explains 19.30 % of the variance. Since the observed distribution of chl a within the DCM cannot be statistically explained without the vorticity, this research sheds light on the impact of the dynamic variables in the distribution of spectral groups at high spatial resolution.
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