Abstract

AbstractWe extracted the harmonic frequency separation (Δf) of Ionospheric Alfvén Resonances (IAR) observed in the Eskdalemuir induction coil magnetometer data for the 9 year data set of 2013–2021. To obtain Δf values, we used a machine learning technique that identifies the harmonics and from this we calculated the average separation. To investigate the climatology of the IAR, we have modeled the Δf of the IAR for the data set using a time of flight calculation with model Alfvén velocity profiles. When analyzing Δf from the model and data, we found that in general they follow the same trends. The modeled Δf and Δf from the data both show an inverse correlation with foF2, which confirms that the frequencies of the IAR are controlled by electron density. It follows that Δf is greater around midnight and during the winter months, due to the decrease in plasma mass density. Variability is also reflected when comparing yearly trends in Δf with the sunspot number; higher frequencies are observed and modeled at low sunspot number. It is difficult to examine trends with instantaneous geomagnetic activity as IAR are not visible in spectrograms when geomagnetic activity is high. We find cases where the difference in measured and modeled Δf is significant, suggesting that the model does not capture short term variations in plasma mass density that influence the IAR during these days. We plan to undertake further modeling of Δf on shorter timescales.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call