Precipitable Water Vapor tracking in the oceans with GNSS and meteorological observations: the Amerigo Vespucci ship World Tour (2023-2025)

The 2023–2025 world tour of the Italian Navy’s Amerigo Vespucci ship offers a unique and remarkable laboratory for multidisciplinary environmental observations over the global oceans, where direct measurements remain extremely limited. Among the various research activities conducted onboard by the Sea Study Center of Genoa University, Precipitable Water Vapor (PWV) evaluations contribute to advancing the understanding of marine atmospheric processes. PWV plays a central role in regulating atmospheric moisture, influencing convection, and shaping the development of extreme precipitation events; yet its variability over the open sea remains poorly constrained due to the limited availability of continuous measurement platforms. As the ship circumnavigates the globe, it continuously records data through an onboard Global Navigation Satellite System (GNSS) and weather station system, transforming the ship into a moving atmospheric observatory. As known, the GNSS observations are influenced by the presence of troposphere, which influence is parametrized through the Zenith Total Delay (ZTD). In the present work, ZTD is estimated with Precise Point Positioning (PPP) strategy. PWV is then obtained using well-established relations, combining ZTD estimates with onboard pressure and temperature measurements. A key innovation of this work is the creation of a global, georeferenced PWV database derived exclusively from ship-based observations, considering the complexities introduced by ship motion, sensor integration, and highly variable marine environments. This dataset is expected to represent a useful contribution to study the meteorological models at sea. The present work represents a first approach for comparing GNSS and Numerical Weather Prediction (NWP) model-derived PWV values, to assess their consistency, quantify uncertainties, and evaluate the potential of assimilating ship-based PWV observations into operational forecasting systems.