The GNSS for Meteorology (G4M) Procedure and Its Application to Four Significant Weather Events

The authors conceived the GNSS for Meteorology (G4M) procedure to remote-sense the Precipitable Water Vapor (PWV) content in atmosphere with the aim to detect severe meteorological phenomena. It can be applied over an orographically complex area, exploiting existing networks of Global Navigation Satellite System (GNSS) Permanent Stations (PSs) and spread meteorological sensors, not necessarily co-located. The results of a posteriori analysis of four significant meteorological events are here presented, also in comparison with rain gauge data, to show the effectiveness of the method. The potentiality of G4M to detect and locate in space and time intense rainfall events is highlighted. The upcoming application of G4M in near-real time could provide a valuable support to existing Decision Support System for meteorological alerts

The amazon dense gnss meteorological network a new approach for examining water vapor and deep convection interactions in the tropics

The Amazon Dense Global Navigational Satellite System (GNSS) Meteorological Network ((ADGMN) provides high spatiotemporal resolution, all-weather precipitable water vapor for studying the evolution of continental tropical and sea-breeze convective regimes of Amazonia. The ADGMN campaign consisted of two experiments: a 6-week campaign in and around Belem, which coincided with the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (CHUVA) and a 1-yr campaign in and around Manaus. The Belem network was composed of 15 GNSS/meteorological stations that provided high-frequency (5 min) PWV data as well as surface meteorological variables For the 6-week duration of the Belem experiment, days were categorized as convective (22 days) or nonconvective (19 days) based solely on a minimum cloud-top temperature of 240 K or below over the central portion of the network and a report of precipitation at at least one site during the afternoon or evening. The Manaus network commenced in April 2011 with 12 GNSS meteorological stations. Local circulations in Manaus driven by anthropogenic deforestation have, in particular, received attention

The amazon dense gnss meteorological network a new approach for examining water vapor and deep convection interactions in the tropics

The Amazon Dense Global Navigational Satellite System (GNSS) Meteorological Network ((ADGMN) provides high spatiotemporal resolution, all-weather precipitable water vapor for studying the evolution of continental tropical and sea-breeze convective regimes of Amazonia. The ADGMN campaign consisted of two experiments: a 6-week campaign in and around Belem, which coincided with the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (CHUVA) and a 1-yr campaign in and around Manaus. The Belem network was composed of 15 GNSS/meteorological stations that provided high-frequency (5 min) PWV data as well as surface meteorological variables For the 6-week duration of the Belem experiment, days were categorized as convective (22 days) or nonconvective (19 days) based solely on a minimum cloud-top temperature of 240 K or below over the central portion of the network and a report of precipitation at at least one site during the afternoon or evening. The Manaus network commenced in April 2011 with 12 GNSS meteorological stations. Local circulations in Manaus driven by anthropogenic deforestation have, in particular, received attention

Tracking Hurricanes using GPS atmospheric precipitable water vapor field

Tropical cyclones are one of the most powerful severe weather events that produce devastating socioeconomic and environmental impacts in the areas they strike. Therefore, monitoring and tracking of the arrival times and path of the tropical cyclones are extremely valuable in providing early warning to the public and governments. Hurricane Florence struck the East cost of USA in 2018 and offers an outstanding case study. We employed Global Positioning System (GPS) derived precipitable water vapor (PWV) data to track and investigate the characteristics of storm occurrences in their spatial and temporal distribution using a dense ground network of permanent GPS stations. Our findings indicate that a rise in GPS-derived PWV occurred several hours before Florence’s manifestation. Also, we compared the temporal distribution of the GPS-derived PWV content with the precipitation value for days when the storm appeared in the area under influence. The study will contribute to quantitative assessment of the complementary GPS tropospheric products in hurricane monitoring and tracking using GPS-derived water vapor evolution from a dense network of permanent GPS station