In being at the base of the marine food web, phytoplankton is particularly important for marine ecosystem functioning (e.g., biodiversity). Strong anthropization, over-exploitation of natural resources, and climate change affect the natural amount of phytoplankton and, therefore, represent a continuous threat to the biodiversity in marine waters. In particular, a concerning risks for coastal waters is the increase in nutrient inputs of terrestrial/anthropogenic origin that can lead to undesirable modifications of phytoplankton concentration (i.e., eutrophication). Monitoring chlorophyll (Chl) concentration, which is a proxy of phytoplankton biomass, is an efficient tool for recording and understanding the response of the marine ecosystem to human pressures and thus for detecting eutrophication. Here, we compute Chl trends over the Mediterranean Sea by using satellite data, also highlighting the fact that remote sensing may represent an efficient and reliable solution to synoptically control the “good environmental status” (i.e., the Marine Directive to achieve Good Environmental Status of EU marine waters by 2020) and to assess the application of international regulations and environmental directives. Our methodology includes the use of an ad hoc regional (i.e., Mediterranean) algorithm for Chl concentration retrieval, also accounting for the difference between offshore (i.e., Case I) and coastal (i.e., Case II) waters. We apply the Mann-Kendall test and the Sens’s method for trend estimation to the Chl concentration de-seasonalized monthly time series, as obtained from the X-11 technique. We also provide a preliminary analysis of some particular trends by evaluating their associated inter-annual variability. The high spatial resolution of our approach allows a clear identification of intense trends in those coastal waters that are affected by river outflows. We do not attempt to attribute the observed trends to specific anthropogenic events. However, the trends that we document are consistent with the findings of several previous studies.

This paper focuses on the study of the Tyrrhenian Sea, a subbasin of the western Mediterranean whose surface and near‐surface dynamics are still relatively poorly known, in particular, its southern region. Its circulation is described first by a set of 53 surface drifters deployed in the area between December 2001 and February 2004. In order to supplement the drifter data with continuously and uniformly sampled observations and to characterize the seasonal, as well as higher‐frequency variability of the surface circulation, the Lagrangian analysis was associated to simultaneous satellite remotely sensed altimeter, covering the period 2001–2004. The investigation was based on trajectory analysis and on the computation of the pseudo‐Eulerian statistics using the same binning and space‐time averaging for drifter and altimeter data. The data reveal a complex pattern of the circulation, especially in the southern region of the Tyrrhenian, dominated by semipermanent recirculations and transient features, which sometimes makes it difficult to identify a consistent mean flow, while the northern subbasin is characterized by a pair composed of cyclonic and anticyclonic circulations known in the literature as the North Tyrrhenian Cyclone and North Tyrrhenian Anticyclone. The pseudo‐Eulerian statistics computed with the two data sets evidenced the representativeness of a joint analysis of altimeter and drifter data and yielded useful indications about proper preliminary preprocessing and resampling procedures, so as to make the comparison statistically sound.

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Operational oceanography products have been used to define the Marine Strategy Framework Directive (MSFD) good environmental status (GES) relative to the Italian marine ecosystem subregions. Observations include sea surface temperature (SST), winds and chlorophyll Mediterranean Sea satellite products and Italian national tide gauge network winds. These were used to obtain SST seasonal climatology data and trends, 90th percentile of chlorophyll climatology data and SST and wind coastal upwelling indices. Also, Eulerian and Lagrangian circulation models have been used to map the residence time (RT) of Lagrangian particles in the marine subregions, which mimics pollutant dispersion capability at a given location and time.

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