Estimating atmospheric precipitable water vapor in northern Morocco: A ground-based GNSS approach

Abstract

The application of Global Navigation Satellite System (GNSS) techniques to ascertain atmospheric water vapor content can provide valuable meteorological data. This method offers both high spatial and temporal resolution, enabling precise measurement of atmospheric conditions. By leveraging the physical properties of the electromagnetic signals transmitted by GNSS satellites, which experience delays when traversing atmospheric layers between satellites and Continuously Operating Reference Stations (CORS), it becomes possible to measure the zenith total delay (ZTD) for each GNSS receiver. This delay can then be converted into atmospheric precipitable water vapor (PWV) using an integrated mapping function. This study aims to estimate atmospheric precipitable water vapor in the northeastern part of Morocco (specifically the Tangier–Tetouan–Al Hoceima region) utilizing ground-based GNSS techniques. Data were collected from nine different GNSS stations covering the study area of 17,252 km² over one month (February 1 to March 4, 2023). The data underwent processing using the high-accuracy GNSS software GAMIT/GLOBK. To validate the results, PWV values obtained from each station were compared with meteorological data collected from nearby meteorological stations during the same period, and compared to ERA5 reanalysis numerical weather model. The validation process revealed favorable results, evidenced by a reasonable spatial distribution of PWV. There were significant increases in the troposphere before significant rainfall, followed by a decrease after the rainfall. For representation, Geographic Information System (GIS) software, was employed for modeling and cartographic representation, illustrating the spatial distribution of atmospheric PWV over time. This study provides evidence of the effectiveness of ground-based GNSS techniques not only in precise positioning and velocity determination but also in weather forecasting. Furthermore, it underscores the value of GNSS as a reliable source of meteorological information in regions lacking radiosonde stations.