E. G. Thomas
- ORCiD
- https://orcid.org/0000-0001-8036-8793
- OpenAlex ID
- https://openalex.org/A5078281239 (API record)
Associated Concepts [?]
- Geology
- Physics
- Geography
- Geophysics
- Astronomy
- Quantum mechanics
- Ionosphere
- Meteorology
- Computer science
- Engineering
- Plasma
- Nuclear physics
- Magnetic field
- Geodesy
- Solar wind
- Atmospheric sciences
- Telecommunications
- Earth's magnetic field
- Aerospace engineering
- Oceanography
- Environmental science
- Climatology
- Geomagnetic storm
- Operating system
- Remote sensing
Authored Works
sorted by decreasing year, and then by display-name
- SuperDARN Iceland: First Results
- Subauroral and midlatitude traveling ionospheric disturbances (TIDs) in the vicinity of storm enhanced density (SED) and subauroral polarization stream (SAPS)
- Remote Sensing of Arctic Sea Ice Using the Super Dual Auroral Radar Network: New Results and Data Products
- Application of SuperDARN Assimilative Mapping Technique to TS18 Plasma Convection Model
- Towards a multi-scale predictive model of the high-latitude ionospheric convection
- Sustained Observations of Arctic Sea Ice Using the Super Dual Auroral Radar Network: First Results
- Solar Wind Alfven Waves Coupling to the M-I-T System Generating Polar Cap Patches and Traveling Ionospheric Disturbances during Geomagnetic Storms
- Monitoring auroral and polar precipitation and their associated scintillation with GNSS networks combined with all-sky imager and SuperDARN observations
- Isolating and quantifying the effect of lobe reconnection on high latitude ionospheric convection during IMF By dominated periods
- Ionospheric Sounding with SuperDARN HF Radars
- Hemispheric differences and Asymmetries Observed in High-Latitude Ionosphere with GNSS TEC and SuperDARN
- GNSS monitoring of traveling ionospheric disturbances excited by geospace and terrestrial weather
- Error Covariance Matrix of the TS18 Ionospheric Convection Model for Use in Assimilative Mapping Procedures
- Characterization of SuperDARN Backscatter Observations using Machine Learning Algorithms
- Amateur Radio Communications as a Novel Sensor of Large Scale Traveling Ionospheric Disturbances
Linked Co-Authors
- A. G. Burrell
- A. J. Coster
- A. M. Keesee
- Anders Ohma
- B. J. Anderson
- B. Kunduri
- Donald Hampton
- Doğacan Öztürk
- Ercha Aa
- G. W. Perry
- H. K. Connor
- H. Kil
- J. B. Baker
- J. D. Huba
- J. M. Ruohoniemi
- J. M. Weygand
- Jone Peter Reistad
- Juha Vierinen
- K. A. McWilliams
- N. A. Frissell
- Nikolai Østgaard
- P. J. Erickson
- P. Prikryl
- Robert B. Kerr
- S. R. Kaeppler
- Shibaji Chakraborty
- Shun‐Rong Zhang
- Spencer Hatch
- Xueling Shi
- Y. Nishimura
- Yue Deng
- Л. П. Гончаренко
Linked Collaborating Institutions
- Boston University, Massachusetts
- British Antarctic Survey
- Dartmouth College, New Hampshire
- Haystack Observatory
- Johns Hopkins University, Applied Physics Laboratory
- La Trobe University, Australia
- Nagoya University, Japan
- New Jersey Institute of Technology
- Rice University, Texas
- Stanford Research Institute, California
- U.S. Department of the Navy, Naval Research Laboratory, Washington DC
- University of Alabama, Tuscaloosa
- University of Alaska, Fairbanks
- University of Bergen, Department of Physics
- University of Bergen, Norway
- University of Calgary, Canada
- University of California, Los Angeles
- University of Colorado, Boulder
- University of New Brunswick, Canada
- University of New Hampshire
- University of Saskatchewan, Canada
- University of Texas, Arlington
- University of Tromso, Norway
- Virginia Polytechnic Institute and State University
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