Weather and sea state observations and modeling in the Gulf of Naples in support of sustainable maritime mobility

Environmental concerns and greenhouse gas emissions are driving policymakers and scientists to focus on improving waterborne transport efficiency. Accurate knowledge of the sea state and weather conditions is crucial for enhancing maritime transport efficiency and developing innovative technologies that could facilitate better management of ships and their subsystems during offshore and coastal operations. In this regard, the University of Naples Parthenope joins the National Centre for Sustainable Mobility (CNMOST) providing weather and sea state observations and forecast with two main aims: to develop a digital twin model of ship and marine environment and to provide informations to autonomous navigation system and vehicles. The digital twin activities will be useful to replicate the behavior of the ship in its operating environment, enabling understanding of how the ship will react in different situations, such as varying or even extreme environmental conditions. This technology allows ship managers to test onboard performance and conditions, preempt breakdowns and malfunctions, and make informed decisions regarding crew management and maintenance activities under different scenarios. On the other hand, marine and atmospheric observations and forecast will be used in support of the creation of an autonomous navigation system to enhance navigation safety and situational awareness, improve passenger comfort, and optimize the ship's route, thereby reducing fuel consumption and emission. To achieve these goals, the need for a dedicated test area to validate these innovative technologies is crucial. In this context, the existing monitoring network of the Gulf of Naples of the University Parthenope, widely used for the study of sea coastal processes of the region, has been further extended with new devices. The network comprises advanced meteo-oceanographic technologies e.g., a coastal high-frequency radar system, a strategic weather stations network, an unmanned marine glider for high-resolution physical and biological data collection, tidegauges, hydrophones, wavebuoy and multi-parameter probe for comprehensive data gathering.  Furthermore, a state-of-the-art high resolution regional ocean model (ROMS) and atmospheric forecasting chain (WRF) have been implemented to provide sea/weather real-time data and predictions (meteo.uniparthenope.it). Both products represent strategic information for advanced decision support systems and improved situational awareness for ship management and autonomous marine vehicles, providing insights into the external disturbances that affect the ship dynamic with consequences on fuel consumption, safety, and comfort. By employing this comprehensive network, the crucial data needed to optimize maritime operations and minimize its environmental impact are collected.

Acknowledgments
This work was supported by the European Union – NextGenerationEU. Piano Nazionale di Ripresa e Resilienza, Missione 4 Componente 2 Investimento 1.4 “Potenziamento strutture di ricerca e creazione di "campioni nazionali di R&S" su alcune Key Enabling Technologies”.  Code CN00000023 – Title: “Sustainable Mobility Center (Centro Nazionale per la Mobilità Sostenibile – CNMS)”, Spoke 3 Waterways, WP 3 Toward Autonomous Navigation.