High-resolution station-based diurnal ionospheric total electron content (TEC) from dual-frequency GPS observations


ÇEPNİ M. S. , Potts L. V. , Miima J. B.

SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS, cilt.11, ss.520-528, 2013 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 11 Konu: 9
  • Basım Tarihi: 2013
  • Doi Numarası: 10.1002/swe.20093
  • Dergi Adı: SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS
  • Sayfa Sayıları: ss.520-528

Özet

Total electron content (TEC) estimates derived from Global Navigation Satellite System (GNSS) signal delays provide a rich source of information about the Earth's ionosphere. Networks of Global Positioning System (GPS) receivers data can be used to represent the ionosphere by a Global Ionospheric Map (GIM). Data input for GIMs is dual-frequency GNSS-only or a mixture of GNSS and altimetry observations. Parameterization of GNSS-only GIMs approaches the ionosphere as a single-layer model (SLM) to determine GPS TEC models over a region. Limitations in GNSS-only GIM TEC are due largely to the nonhomogenous global distribution of GPS tracking stations with large data gaps over the oceans. The utility of slant GPS ionospheric-induced path delays for high temporal resolution from a single-station data rate offers better representation of TEC over a small region. A station-based vertical TEC (TECV) approach modifies the traditional single-layer model (SLM) GPS TEC method by introducing a zenith angle weighting (ZAW) filter to capture signal delays from mostly near-zenith satellite passes. Comparison with GIMs shows the station-dependent TEC (SD-TEC) model exhibits robust performance under variable space weather conditions. The SD-TEC model was applied to investigate ionospheric TEC variability during the geomagnetic storm event of 9 March 2012 at midlatitude station NJJJ located in New Jersey, USA. The high temporal resolution TEC results suggest TEC production and loss rate differences before, during, and after the storm.