Understanding how long water is retained in an estuary and how quickly it is completely flushed is essential to estimate an estuary’s health in areas with significant pollutant loadings. The present study analyses the effect of five different Tagus River discharge scenarios ranging from low to extreme on residence time (RT), exposure time (ET) and integrated water fractions inside pre-established Tagus estuary areas, to identify its most vulnerable areas to pollution. The 3D version of the MOHID hydrodynamic model coupled to a lagrangian tool was used. The increase of the river discharge generated high current velocities which, in turn, led to an increased rate of tracers leaving the estuary. As a consequence, RT and ET decreased from 59 to 3.5 days under a low and extreme river discharge scenario, respectively. Under a low river discharge, significant differences were observed between RT and ET in the areas located in the main body of the estuary and in the bays. As river discharge increased, RT and ET decreased in all areas of the estuary and those differences faded, with the greatest differences observed in the areas situated along the south margin. In general, results showed that with high river discharges the tracers released in the upper estuary are spread throughout the estuary, but mainly in downstream areas. However, when the river discharge reached exceptionally high values, local eddies were formed, leading to the retention of the tracers in the estuary’s south margin and inner bays. The results in this study allowed to identify the most vulnerable areas within the estuary as a function of the river discharge.
<div> <p><span data-contrast="none">Remote sensing plays a vital role in understanding and managing the oceans. This technology is used to observe and monitor the ocean's physical, chemical, and biological properties, allowing scientists to detect large-scale changes in the marine environment</span><span data-contrast="none">,</span><span data-contrast="none"> such as currents, sea surface temperature, and marine life populations. This data can then be utilized to track changes in the marine environment, assess the ocean&#8217;s health, and identify areas that require conservation efforts.</span><span data-ccp-props="{">&#160;</span></p> </div> <div> <p><span data-contrast="none">In oceanography, a front is a boundary between two distinct water masses with different properties, such as temperature, salinity, and density. </span><span data-contrast="none">These fronts are critical scientific phenomena and have a cascade of events of significant importance to the fishing, marine biology, shipping, and logistics industries. For example, upwelling fronts are typically sites of strong vertical movements that bring cold, nutrient-rich water to the euphotic zone. This phenomenon is a primary factor controlling phytoplankton growth, which is the foundation of the marine food chain. It can also influence the concentration of floating marine litter, plastic, and other human-made objects.</span><span data-contrast="none">&#8239;</span><span data-ccp-props="{">&#160;</span></p> </div> <div> <p><span data-contrast="none">Our work comprised the search, revision, and implementation of three algorithms to detect oceanic fronts through the model and satellite sea surface temperature (SST) data. The chosen algorithms</span><span data-contrast="none">,</span><span data-contrast="none"> Canny, Belkin O&#8217;Reilly, and Cayula-Cornillon</span><span data-contrast="none">,</span><span data-contrast="none"> use SST data to provide historical frontal probability maps and near-real-time daily fronts identification.</span><span data-contrast="none"> These algorithms were aggregated, simplified, and adapted for use in the Python programming language.</span><span data-ccp-props="{">&#160;</span></p> </div> <div> <p><span data-contrast="none">Establishing free and open repositories helps to spur research, innovation</span><span data-contrast="none">,</span><span data-contrast="none"> and development. That&#8217;s why we have created the following public repository </span><span data-contrast="none">(</span><span data-contrast="none">https://github.com/CoLAB-ATLANTIC/JUNO</span><span data-contrast="none">)</span><span data-contrast="none">, </span><span data-contrast="none">which includes a set of notebooks outlining the step-by-step process for obtaining frontal probability or daily fronts maps using each of the three algorithms. The method consists of downloading the data (MUR or CMEMS), applying the algorithms, and saving the results in a NetCDF file.</span><span data-ccp-props="{">&#160;</span></p> </div> <div> <p><span data-contrast="none">This repository will help scientists, researchers, and business people understand the ocean&#8217;s dynamics and make front detection more accessible. Through this repository, our work is making strides to advance the oceanography field and make ocean research more efficient and available to everyone.</span></p> </div>
Este trabalho tem como objetivo estudar a variabilidade da energia cinética turbulenta (EKE) oceânica na região da Confluência Brasil-Malvinas (CBM). Dados altimétricos de anomalia de velocidade geostróficas foram utilizados para a estimativa da EKE e, ao mesmo tempo, o produto altimétrico de topografia oceânica também foi empregado para a investigação de feições oceanográficas na região de estudo, entre 1992 e 2011. A variabilidade espacial foi investigada a partir de análises de composições em diferentes estágios energéticos da EKE (baixa, média e alta). Foram utilizadas tendências lineares, análises espectrais e de ondeletas para avaliar a variabilidade temporal desta forma de energia. Ainda, foram feitas correlações cruzadas em relação a índices de modos de variabilidade climática. De maneira geral, foi observado que no regime de baixas energias a corrente atinge sua maior extensão ao sul e o regime mais energético ficou marcado pela presença de vórtices liberados pela corrente seguido de retração do primeiro meandro de retroflexão. A EKE teve tendência de aumento significativa ao longo dos 18 anos estudados, com uma taxa positiva de 0,23 cm² s-2 por mês. Esse aumento pode ter ocorrido devido a duas causas: (i) o aumento da atividade de mesoescala na região e (ii) a uma variabilidade interanual da posição média da CBM, relacionada com a intensificação dos campos de ventos de larga escala do hemisfério Sul.
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