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We investigated the amplitude of medium scale traveling ionospheric disturbances (MSTIDs, with periods 25–100 min) and their dependence on the solar activity using 16 years data of the rapid run‐ionosonde operating at high latitudes (67°$67{}^{\circ}$N, Sodankylä, Finland). A deep learning neural network was applied to ionograms to extract critical frequency of the F2 region (foF2) with a 1 min time resolution. Then, we analyzed the relative amplitude of MSTIDs (i.e., 2δ$2\delta $foF2/foF2), which corresponds to the amplitude of atmospheric gravity waves (AGWs) causing MSTIDs. The amplitude of AGWs propagating upward increases with height due to the decreasing density of the air, and hmF2 varies depending on local time, seasonal and solar activity conditions. To account for this effect, we calculated a corrected MSTID amplitude by normalizing the relative amplitude for the air density at the hmF2. The corrected amplitudes show no clear dependence on F10.7 during winter (0–12 UT), equinox (20‐01 UT) and summer (19‐01 UT), while a positive dependence of corrected amplitudes on F10.7 was observed during winter and equinox, in 14–22 UT and 15–19 UT, respectively. Corresponding to the dependence behaviors of corrected and relative amplitudes, two likely mechanisms of MSTIDs, AGWs from the lower atmosphere and auroral sources, are inferred. Their subsequent roles in the solar activity dependence of MSTID amplitudes were separately discussed, although in reality, the observed dependence is complex and often involves several mechanisms together. HF radio frequencies used for ground and/or space‐ground communications and navigation systems often face challenges due to traveling ionospheric disturbances (TIDs), which can degrade the propagation of radio signals. Employing deep learning for rapid‐run ionosonde data enabled us to monitor TIDs at Sodankylä Geophysical Observatory (SGO) effectively. Daytime TID occurrences are often associated with disturbances triggered from the lower atmosphere (AGWs). However, the increase in hmF2, which reduces the likelihood of AGWs initiated from the lower atmosphere reaching the region of peak ionization, and the expansion of the auroral oval due to frequent substorms, shift the nighttime triggers to auroral electrodynamics in high latitude regions. In this paper, we examine the dependence of MSTID amplitudes on solar activity after applying a new correction approach. foF2 obtained from 1 min ionograms through deep learning enabled us to conduct long‐term MSTID investigations in high latitudesCorrection of MSTID amplitudes to the neutral density level at different hmF2 altitudes properly describes the solar activity dependenceCorresponding to the causing mechanisms, the high‐latitude corrected MSTID amplitudes infer different types of dependence on solar activity foF2 obtained from 1 min ionograms through deep learning enabled us to conduct long‐term MSTID investigations in high latitudes Correction of MSTID amplitudes to the neutral density level at different hmF2 altitudes properly describes the solar activity dependence Corresponding to the causing mechanisms, the high‐latitude corrected MSTID amplitudes infer different types of dependence on solar activity

The potential of deep learning for the investigation of medium scale traveling ionospheric disturbances (MSTIDs) has been exploited through the Sodankylä rapid‐run ionosonde in this statistical study. The complementing observations of the Sodankylä ionosonde with those of the Sodankylä meteor radar reveals the diurnal and seasonal occurrence rate of high‐latitude MSTIDs in the recent low solar activity period, 2018–2020. In our results, the daytime, nighttime and dusk MSTIDs are predominantly identified during winter, summer, and equinoctial months, respectively. The winter daytime higher (lower) occurrence rate is well correlated with the lower (higher) altitude of the height of the F2‐layer peak (hmF2), and the low occurrence rate of the summer daytime is well correlated with the mesosphere‐lower‐thermosphere wind shear and higher gradient of temperature. Relatively high occurrence rate (>0.4) of summer nighttime MSTIDs has a general—but not one‐to‐one agreement—with post‐noon to evening IU (eastward auroral current index) inferred ionospheric conductivity. Rather, we see a one‐to‐one relationship between the summer nighttime MSTIDs and zonal wind shear suggesting that the wind shear‐induced electrodynamic processes could play significant roles for higher occurrence rate of MSTIDs. Furthermore, significant MSTIDs with ∼0.4 occurrence rate are so far revealed during spring and autumn transition periods. The enhanced nighttime MSTID amplitudes during the equinox are observed to be well correlated with IL index (westward auroral current indicator) suggesting that the particle precipitation during substorms could be the primary cause. Deep neural networking approach has shown its great potential for ionosonde driven MSTID studiesDaytime (nighttime) MSTIDs result from lower (upper) atmospheric/ionospheric sourcesIonosonde‐Meteor radar collocated measurements reveal excellent agreement to MSTID studies Deep neural networking approach has shown its great potential for ionosonde driven MSTID studies Daytime (nighttime) MSTIDs result from lower (upper) atmospheric/ionospheric sources Ionosonde‐Meteor radar collocated measurements reveal excellent agreement to MSTID studies