Speaker
Description
Understanding and predicting magnetospheric response to variations in interplanetary conditions is a central goal of space physics. Prominent interplanetary structures, such as Coronal Mass Ejections (CMEs) and Corotating Interaction Regions (CIRs), are the main drivers of the geomagnetic storms, which are classified according to the magnitude of Earth’s magnetic field perturbations. These disturbances are quantified by the Dst index, and the storms are classified as weak (Dst between -30 and -50 nT), moderate (Dst between -50 and -100 nT), intense (Dst between -100 and -250 nT) and super-intense (Dst lower than -250 nT). During intense and super-intense storms, the Earth’s magnetopause undergoes significant compression, enhancing energy transfer into the magnetosphere . Several theoretical models have been developed to describe magnetopause dynamics, for example the model proposed by Shue et al., (1997, 1998), which estimates the magnetopause location as function of solar wind parameters. . Although the model is widely used in the space physics field, it still has limitations that can be evidenced especially during extreme events. The goal of this work is to analyse the magnetopause variation during intense and super-intense geomagnetic storms. The analysis uses in situ satellite data from solar wind, magnetosheath, and inner magnetosphere. At this point the extreme events were identified and categorized. OMNI dataset are used for an initial characterization of the events and identification of the driving interplanetary structures. Magnetopause crossings are identified using data from MMS, THEMIS, and GOES and compared with the empirical model predictions to investigate its limitations. The data are obtained using the Python version of the SPEDAS software (PySPEDAS), which was developed for the analysis and visualization of data from various space missions.