Near-real-time VTEC maps: new contribution for Latin America Space Weather (1909.05213v1)

Abstract: The development of regional services able to provide ionospheric vertical totalelectron content (VTEC) maps and ionospheric indexes with a high spatialresolution, and in near-real-time, are of great importance for both civilianapplications and the research community. We provide here the methodolo-gies, and an assessment, of such a system. It relies on the public GlobalNavigational Satellite Systems (GNSS) infrastructure in South America, in-corporates data from multiple constellations (currently GPS, GLONASS,Galileo and BeiDou), employs multiple frequencies, and produces continen-tal wide VTEC maps with a latency of just a few minutes. To assess theability of our system to model the ionospheric behavior we performed a year-round intercomparison between our near-real-time regional VTEC maps, andVTEC maps of verified quality produced by several referent analysis centers,resulting in mean biases lower than 1 TEC units (TECU). Also, the evalua-tion of our products against direct and independent GNSS-based slant TECmeasurements shows RMS values better than 1 TECU. In turn, ionospheric W-index maps were generated, for calm and disturbed geomagneticscenarios, solely employing our quality verified VTEC maps. The spatial rep-resentation of these W-index maps reflects the state of the ionosphere, with aresolution of 0.5x0.5 degrees. Finally, we conclude that our products, com-puted every 15 minutes, do provide an excellent spatial representation of theregional TEC, and are able to provide the bases for the possible computationof ionospheric W-index maps, also in near-real-time

• The paper presents a novel near-real-time system generating high-resolution vertical total electron content (VTEC) maps for Central and South America using multi-GNSS data.
• Validation using intercomparison and independent slant TEC measurements shows high accuracy with mean biases and RMS errors below 1 TEC unit.
• The study introduces the W-index, an ionospheric weather index derived from these VTEC maps, providing enhanced monitoring of space weather disturbances for various applications.

Near-real-time VTEC Maps: A New Contribution for Latin America's Space Weather

The paper presents a novel approach for developing a near-real-time ionospheric monitoring system that generates vertical total electron content (VTEC) maps for Central and South America. Utilizing extensive data from multiple global navigational satellite systems (GNSS) such as GPS, GLONASS, Galileo, and BeiDou, the system produces high-resolution VTEC maps with minimal latency—an essential advancement for both civilian utility and academic research.

The GNSS infrastructure serves as a robust foundation for this system, which integrates multiple frequency observations to construct continental VTEC maps. The described methodology involves preprocessing and precision calibration techniques to ensure accuracy in the generated maps. The paper further elaborates on two key validation strategies: intercomparison with other established VTEC maps from various analysis centers and independent validation using slant TEC measurements. The results are promising, indicating mean biases less than 1 TEC unit and root mean square (RMS) errors below 1 TEC unit. These benchmarks suggest that the generated VTEC maps achieve commendable accuracy in mapping regional ionospheric behaviors.

An integral feature of the paper is the development of the W-index, an ionospheric weather index generated exclusively from the VTEC maps for various geomagnetic conditions. This index provides a granular representation of ionospheric disturbances, with a resolution of 0.5 x 0.5 degrees. The W-index allows for enhanced monitoring of space weather events, serving as an informative tool for telecommunications, navigation, and high-frequency communication systems, which are sensitive to ionospheric variations.

From a theoretical standpoint, this research enriches the understanding of ionospheric dynamics over the South American region—a crucial aspect given the increasing significance of this area in space weather studies. On a practical level, the near-real-time capability of this system significantly benefits applications reliant on accurate, up-to-date ionospheric data.

Future directions could involve extending this system by incorporating more data streams and additional geographical regions, improving algorithmic efficiency for real-time computation, and exploring machine learning techniques to refine or predict ionospheric conditions. As the dependency on reliable GNSS data grows for various technologies and sectors, advancements like these are pivotal in fostering resilient systems against space weather perturbations. Such developments indicate a broader potential for integration into global systems aimed at space weather forecasting and management.