Welcome to the UNB Radio and Space Physics Laboratory (RSPL)
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Research Areas
| Instrumentation | Ionospheric Model Development | Fundamental Research |
| • Canadian Advanced Digital Ionosonde (CADI) | • Empirical Canadian High Arctic Ionospheric Model (E-CHAIM) | • Physics of Solar - Terrestrial interaction |
| • Sanimut-based Ionosonde | • Assimilative Canadian High Arctic Ionospheric Model (A-CHAIM) | • Vertical coupling in the atmosphere |
| • Broadband RF receivers | • Canadian High Arctic Scintillation Model (CHASM) | • Metrology |
| • GNSS receiver technology | • Data science |
Current state of the ionosphere:
| NmF2 | TEC | hmF2 |
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Projects
Most Recent Publications
- Mackovjak, ., Kostárová, S., Chum, J., Schmidt, C., Hannawald, P., Wüst, S., Küchelbacher, L., Truhlík, V., Knížová, P., Urbář, J., Randuška, L., Štempel, F., Kubančák, J., (2026), Dataset of Quiet Space Weather Periods for Ionospheric Studies, Earth and Space Science. American Geophysical Union (AGU). link
- Zhan, Y., Xing, Z., Xu, T., Zhang, Q., Wang, Y., Yang, Q., Qiao, F., Ma, Y., Lu, S., Fang, Y., (2026), Prediction of Arctic Ionospheric Scintillation Using Stacked Machine Learning, JGR Space Physics. American Geophysical Union (AGU). link
- Gurney, E., Themens, D., Brown, M., Elvidge, S., (2026), Validation of Ionospheric Models at Mid‐ and High‐Latitudes: Climatological Performance of WACCM‐X (SD) and TIE‐GCM in foF2, Space Weather. American Geophysical Union (AGU). link
- Wang, Y., Zhang, Q., Chen, Y., Ning, Y., Xing, Z., Ma, Y., Zhao, L., Wang, X., Lu, S., Xiu, Z., Zhang, D., Zhang, S., Jayachandran, P., (2026), Ionospheric Responses to the Recovery Phase of May 2024 Superstorm Over Shandong Peninsula of China, JGR Space Physics. American Geophysical Union (AGU). link
- Thakrar, C., Gachancipa, N., Deshpande, K., Bals, A., Paxton, L., (2026), Categorizing Characteristic Regions of High‐Latitude Scintillations Using a Combination of Isolation Forest and Neural Network Machine Learning Algorithms, Journal of Geophysical Research: Machine Learning and Computation. American Geophysical Union (AGU). link