“…Sánchez-Garrido et al (2013) studied the collapse of the WAG through a numerical approach and, consequently, the enhancement of positive vorticity in the easternmost Strait as the cause for the AJ-WAG system breakdown. The AJ positive vorticity can also be raised by both tides (Romero-Cózar et al, 2021) and flows driven by atmospheric pressure. The water mass composition of the Mediterranean outflow (e.g., Millot, 2014;Millot & García-Lafuente, 2011;Naranjo et al, 2015) is affected by the state of the WAG (García-Lafuente et al, 2017).…”
Atlantic and Mediterranean waters encounter in the Strait of Gibraltar (Figure 1), where the fresher and lighter Atlantic Water (AW) flows onto the saltier and denser Mediterranean Water (MW) (Lacombe & Richez, 1982). Both water masses create the Atlantic Mediterranean Interface (AMI) with a thickness of 60-100 m, which deepens on the western side (400 m) and is shallower (100 m) on the eastern side (Bray et al., 1995). At the easternmost side of the Strait, AMI has been related with the isohaline 37.2 (García-Lafuente et al., 2013), and its position helps describe the biological processes taking place across the Strait
“…Sánchez-Garrido et al (2013) studied the collapse of the WAG through a numerical approach and, consequently, the enhancement of positive vorticity in the easternmost Strait as the cause for the AJ-WAG system breakdown. The AJ positive vorticity can also be raised by both tides (Romero-Cózar et al, 2021) and flows driven by atmospheric pressure. The water mass composition of the Mediterranean outflow (e.g., Millot, 2014;Millot & García-Lafuente, 2011;Naranjo et al, 2015) is affected by the state of the WAG (García-Lafuente et al, 2017).…”
Atlantic and Mediterranean waters encounter in the Strait of Gibraltar (Figure 1), where the fresher and lighter Atlantic Water (AW) flows onto the saltier and denser Mediterranean Water (MW) (Lacombe & Richez, 1982). Both water masses create the Atlantic Mediterranean Interface (AMI) with a thickness of 60-100 m, which deepens on the western side (400 m) and is shallower (100 m) on the eastern side (Bray et al., 1995). At the easternmost side of the Strait, AMI has been related with the isohaline 37.2 (García-Lafuente et al., 2013), and its position helps describe the biological processes taking place across the Strait
“…The high frequency (HF) radar [ 12 , 13 , 14 , 15 , 16 ] is another example for ocean surface current measurements. There are about 150 HF radars along the coast of the U.S., including the Great Lakes, and the data are reported in real-time to the U.S.…”
Acoustic Doppler current profilers (ADCP) are quasi-remote sensing instruments widely used in oceanography to measure velocity profiles continuously. One of the applications is the quantification of land–ocean exchange, which plays a key role in the global cycling of water, heat, and materials. This exchange mostly occurs through estuaries, lagoons, and bays. Studies on the subject thus require that observations of total volume or mass transport can be achieved. Alternatively, numerical modeling is needed for the computation of transport, which, however, also requires that the model is validated properly. Since flows across an estuary, lagoon, or bay are usually non-uniform and point measurements will not be sufficient, continuous measurements across a transect are desired but cannot be performed in the long run due to budget constraints. In this paper, we use a combination of short-term transect-based measurements from a vessel-mounted ADCP and relatively long-term point measurements from a moored ADCP at the bottom to obtain regression coefficients between the transport from the vessel-based observations and the depth-averaged velocity from the bottom-based observations. The method is applied to an Arctic lagoon by using an ADCP mounted on a buoyant platform towed by a small inflatable vessel and another ADCP mounted on a bottom deployed metal frame. The vessel-based measurements were performed continuously for nearly 5 h, which was sufficient to derive a linear regression between the datasets with an R2-value of 0.89. The regression coefficients were in turn applied to the entire time for the moored instrument measurements, which are used in the interpretation of the subtidal transport variations.
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