The main purposes of this paper are to identify and evaluate the oceanic mesoscale features that appear in the Atlantic Ocean eastern boundary. 20-40° N, 19-9° W, using ERS-1 (1992-1993) satellite altimeter data. The sea surface height anomalies and the eddy kinetic energy fields are calculated. High energy values, between 0.03 and 0.05 m2 s-2, are observed with the altimeter data in the Canary region mainly in summer. These maximum values are associated with eddies located downstream of Gran Canaria and Tenerife (Canary Islands). Comparison with in situ measurements provided by the hydrographic surveys from a cruise in summer 1993 around the Canary Islands showed a good agreement. Dynamic heights relative to 300 dbar for August and the altimetric heights from ERS-1 data were averaged over 0.125° boxes for the duration of the cruise. The correlation coefficient was 0.7. Negative anomalies of the sea level calculated from ERS-1 between Cape Yubi and Cape Bojador (26.0°-27.5° N) were obtained in August 1993. Possibly these correspond with filaments from the north-west African upwelling coast. Also, the results of the altimetric data were compared with NOAA AVHRR (Advanced Very High Resolution Radiometer) sea surface temperature (SST) satellite images. A cyclonic and an anticyclonic eddy to the south-west of the island of Gran Canaria were identified during the same period in the SST images
Fractal properties of deep ocean current speed time series, measured at a single-point mooring on the Madeira Abyssal Plain at 1000-and 3000-m depth, are explored over the range between one week and 5 years, by using the detrended fluctuation analysis and multifractal detrended fluctuation analysis methodologies. The detrended fluctuation analysis reveals the existence of two subranges with different scaling behaviors. Long-range temporal correlations following a power law are found in the time-scale range between approximately 50 days and 5 years, while a Brownian motion-type behavior is observed for shorter time scales. The multifractal analysis approach underlines a multifractal structure whose intensity decreases with depth. The analysis of the shuffled and surrogate versions of the original time series shows that multifractality is mainly due to long-range correlations, although there is a weak nonlinear contribution at 1000-m depth, which is confirmed by the detrended fluctuation analysis of volatility time series.
The South Atlantic Ocean plays a key role in the heat exchange of the climate system, as it hosts the returning flow of the Atlantic Meridional Overturning Circulation (AMOC). To gain insights on this role, using data from three hydrographic cruises conducted in the South Atlantic Subtropical gyre at 34.5°S, 24°S, and 10°W, we identify water masses and compute absolute geostrophic circulation using inverse modeling. In the upper layers, the currents describe the South Atlantic anticyclonic gyre with the northwest flowing Benguela Current (26.3 ± 2.0 Sv at 34.5°S, and 21.2 ± 1.8 Sv at 24°S) flowing above the Mid‐Atlantic Ridge (MAR) between 22.4°S and 28.4°S (−19.2 ± 1.4 Sv), and the southward flowing Brazil Current (−16.5 ± 1.3 Sv at 34.5°S, and −7.3 ± 0.9 Sv at 24°S); the deep layers feature the southward transports of Deep Western Boundary Current (−13.9 ± 3.0 Sv at 34.5°S, and −8.7 ± 3.8 Sv at 24°S) and Deep Eastern Boundary Current (−15.1 ± 3.5 Sv at 34.5°S, and −16.3 ± 4.7 Sv at 24°S), with the interbasin west‐to‐east flow close to 24°S (7.5 ± 4.4 Sv); the abyssal waters present northward mass transports through the Argentina Basin (5.6 ± 1.1 Sv at 34.5°S, and 5.8 ± 1.5 Sv at 24°S) and Cape Basin (8.6 ± 3.5 Sv at 34.5°S–3.0 ± 0.8 Sv at 24°S) before returning southward (−2.2 ± 0.7 Sv at 24°S to −7.9 ± 3.6 Sv at 34.5°S), without any interbasin exchange across the MAR. In addition, we compute the upper AMOC strength (14.8 ± 1.0 and 17.5 ± 0.9 Sv), the equatorward heat transport (0.30 ± 0.05 and 0.80 ± 0.05 PW), and the freshwater flux (0.18 ± 0.02 and −0.07 ± 0.02 Sv) at 34.5°S and 24°S, respectively.
The filaments of the African Eastern Boundary Upwelling System (EBUS) are responsible for feeding nutrients to the oligotrophic waters of the northeastern Atlantic. However, turbulent mixing associated with nutrient uplift in filaments is poorly documented and has been mainly evaluated numerically. Using microstructure profiler measurements, we detected enhanced turbulent kinetic energy dissipation rates (ε) within the Cape Ghir upwelling filament. In contrast to previous studies, this enhancement was not related to symmetrical instabilities induced by down-front winds but to an increase in vertical current shear at the base of the mixed layer (hρ). In order to quantify the impact of vertical shear and the influence of the active mixing layer depth (hε) in the filament, a simple one-dimensional (1D) turbulent entrainment approach was used. We found that the effect of turbulent enhancement, together with the isopycnal morphology of the filament front, drove the formation of local positive entrainment zones (Δh=hε−hρ), as hε was deeper than hρ. This provided suitable conditions for the entrainment of cold, nutrient-rich waters from below the filament pycnocline and the upward transport of biophysical properties to the upper boundary layer of the front. We also found that diapycnal nutrient fluxes in stations influenced by the filament (1.35 mmol m-2 d-1) were two orders of magnitude higher than those of stations not affected by the filament front (0.02 mmol m-2 d-1). Despite their importance, the effects of vertical shear and hε have often been neglected in entrainment parameterizations. Thus, a modified entrainment parameterization was adapted to include vertical shear and observed ε, which are overestimated by existing parameterizations. To account for the possible role of internal waves in the generation of vertical shear, we considered internal wave scaling to parameterize the observed dissipation. Using this adapted parameterization, the average entrainment velocities were six times (6 m d-1) higher than those obtained with the classic parameterization (1 m d-1).
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