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Anthropogenic underwater noise is an emergent pollutant. Despite several worldwide monitoring programs, only few data are available for the Mediterranean Sea, one of the global biodiversity hotspots. The results of the first continuous acoustic programme run at a transnational basin scale in the Mediterranean Sea are here presented. Recordings were done from March 2020 to June 2021, including the COVID-19 lockdown, at nine stations in the Northern Adriatic Sea. Spatial-temporal variations of the underwater sound are described, having one third octave band sound pressure levels (SPLs) from 10 Hz to 20 kHz as metrics. Higher and more variable SPLs, mainly related to vessel traffic, were found close to harbours, whereas Natura 2000 stations experienced lower SPLs. Lower values were recorded during the lockdown in five stations. Median yearly SPLs ranged between 64 and 95 as well as 70 and 100 dB re 1 µPa for 63 and 125 Hz bands, respectively. These values are comparable with those previously found in busy shallow EU basins but higher levels are expected during a business-as-usual period. This is a baseline assessment for a highly impacted and environmental valuable area, that needs to be managed in a new sustainable blue growth strategy., (© 2023. The Author(s).)

The protection of marine habitats from human-generated underwater noise is an emerging challenge. Baseline information on sound levels, however, is poorly available, especially in the Mediterranean Sea. To bridge this knowledge gap, the SOUNDSCAPE project ran a basin-scale, cross-national, long-term underwater monitoring in the Northern Adriatic Sea. A network of nine monitoring stations, characterized by different natural conditions and anthropogenic pressures, ensured acoustic data collection from March 2020 to June 2021, including the full lockdown period related to the COVID-19 pandemic. Calibrated stationary recorders featured with an omnidirectional Neptune Sonar D60 Hydrophone recorded continuously 24 h a day (48 kHz sampling rate, 16 bit resolution). Data were analysed to Sound Pressure Levels (SPLs) with a specially developed and validated processing app. Here, we release the dataset composed of 20 and 60 seconds averaged SPLs (one-third octave, base 10) output files and a Python script to postprocess them. This dataset represents a benchmark for scientists and policymakers addressing the risk of noise impacts on marine fauna in the Mediterranean Sea and worldwide., (© 2023. The Author(s).)

An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROMS-derived surface currents. The two systems differ significantly in architecture and algorithms, being based on either unsupervised learning techniques or ocean physics. To compare performance of the two methods, their forecasting skills were tested on independent datasets. The SOM-based forecasting system has a slightly better forecasting skill, especially during strong wind conditions, with potential for further improvement when data sets of higher quality and longer duration are used for training.