Climatology and modeling of ionospheric irregularities over Greenland based on empirical orthogonal function method

This paper addresses the long-term climatology (over two solar cycles) of total electron content (TEC) irregularities from a polar cap station (Thule) using the rate of change of the TEC index (ROTI). The climatology reveals variabilities over different time scales, i.e., solar cycle, seasonal, and...

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Bibliographic Details
Published in:Journal of Space Weather and Space Climate
Main Authors: Jin Yaqi, Clausen Lasse B.N., Miloch Wojciech J., Høeg Per, Jarmołowski Wojciech, Wielgosz Paweł, Paziewski Jacek, Milanowska Beata, Hoque Mainul, Berdermann Jens, Lyu Haixia, Hernández-Pajares Manuel, García-Rigo Alberto
Format: Article in Journal/Newspaper
Language:English
Published: EDP Sciences 2022
Subjects:
ionospheric irregularities
eof
modeling
space weather
roti
Meteorology. Climatology
QC851-999
Greenland
Thule
Online Access:https://doi.org/10.1051/swsc/2022022
https://doaj.org/article/ac2893d29c774d4fa39a8fdc096449e1
Description
Summary:This paper addresses the long-term climatology (over two solar cycles) of total electron content (TEC) irregularities from a polar cap station (Thule) using the rate of change of the TEC index (ROTI). The climatology reveals variabilities over different time scales, i.e., solar cycle, seasonal, and diurnal variations. These variations in different time scales can be explained by different drivers/contributors. The solar activity (represented by the solar radiation index F10.7P) dominates the longest time scale variations. The seasonal variations are controlled by the interplay of the energy input into the polar cap ionosphere and the solar illumination that damps the amplitude of ionospheric irregularities. The diurnal variations (with respect to local time) are controlled by the relative location of the station with respect to the auroral oval. We further decompose the climatology of ionospheric irregularities using the empirical orthogonal function (EOF) method. The first four EOFs could reflect the majority (99.49%) of the total data variability. A climatological model of ionospheric irregularities is developed by fitting the EOF coefficients using three geophysical proxies (namely, F10.7P, Bt, and Dst). The data-model comparison shows satisfactory results with a high Pearson correlation coefficient and adequate errors. Additionally, we modeled the historical ROTI during the modern grand maximum dating back to 1965 and made the prediction during solar cycle 25. In such a way, we can directly compare the climatic variations of the ROTI activity across six solar cycles.

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