14:00 〜 14:15
[PEM12-27] Ionosphere storm perturbations and their correlation to solar wind parameters
★Invited Papers
キーワード：ionosphere, storm, Europe, solar wind
Understanding and predicting ionosphere storms is a major task in ionosphere research, because ionosphere storms are related to manifold types of technical impact (e.g. positioning accuracy, loss of lock, HF communication problems, etc.). Therefore, ionosphere storms and their source mechanisms are a frequent research topic. The main driver for ionosphere storms is the solar wind energy, which is deposited in the geosystem in the ring current, the magnetotail and via Joule heating in the ionosphere. Changes in the ionosphere electron densities are to a major extend driven by changes in the electric fields (e.g. prompt penetration electric field or disturbance dynamo electric field) and changes in the thermosphere dynamics and composition, caused by intense Joule heating in the auroral region. Typically, during ionosphere storms, significant electron density enhancements and depletions occur successively and are dependent on the geographic or geomagnetic location, local time and storm onset time.
In this presentation, we present statistical results of the characteristic storm evolution observed in the Total Electron Content (TEC) in the European region. We use a list of 672 storms, which we distinguish in 12 different classes dependent on season and storm time onset. The results describe a seasonal, storm time and local time dependency of the TEC deviations to quiet conditions. More positive storms can be observed during winter, while summer storms are more characterized by negative storm conditions. The correlation of the positive storm amplitudes with solar wind parameters show significant values, but only for some storm classes (especially those with onset in the morning hours). Often, the correlation values in high- and mid-latitudes differ.
We also present analysis of Large Scale Travelling Ionospheric Disturbances (LSTIDs), which are frequently observed during storms and considered to be an indicator for thermosphere processes contributing to the ionosphere storm condition. LSTIDs are detected by filtering TEC observations. They usually occur at the equatorward boundary of the auroral oval and propagate equatorward. Using a new estimate for the LSTID amplitude, we derive results for the correlation between the LSTID amplitude and typical solar wind and geomagnetic parameters. The results show good correlation of the LSTID amplitude with the solar wind merging electric field, which exceeds the correlation with most geomagnetic parameters, and can be applied to generate LSTID predictions.
In this presentation, we present statistical results of the characteristic storm evolution observed in the Total Electron Content (TEC) in the European region. We use a list of 672 storms, which we distinguish in 12 different classes dependent on season and storm time onset. The results describe a seasonal, storm time and local time dependency of the TEC deviations to quiet conditions. More positive storms can be observed during winter, while summer storms are more characterized by negative storm conditions. The correlation of the positive storm amplitudes with solar wind parameters show significant values, but only for some storm classes (especially those with onset in the morning hours). Often, the correlation values in high- and mid-latitudes differ.
We also present analysis of Large Scale Travelling Ionospheric Disturbances (LSTIDs), which are frequently observed during storms and considered to be an indicator for thermosphere processes contributing to the ionosphere storm condition. LSTIDs are detected by filtering TEC observations. They usually occur at the equatorward boundary of the auroral oval and propagate equatorward. Using a new estimate for the LSTID amplitude, we derive results for the correlation between the LSTID amplitude and typical solar wind and geomagnetic parameters. The results show good correlation of the LSTID amplitude with the solar wind merging electric field, which exceeds the correlation with most geomagnetic parameters, and can be applied to generate LSTID predictions.