# Unveiling the Core Patterns of High-Latitude Electron Density Distribution at Swarm Altitude
## 6 Summary and Conclusions
By integrating these spatiotemporal distributions and energy factors into models, a more precise and comprehensive depiction of the ionosphere could be achieved. In turn, this advance could lead to more accurate prediction of forthcoming ionospheric conditions. Indeed, these findings could be similarly applied to the recent development of a prediction model of Total Electron Content (TEC) derived from GPS data [37]. In this case, a hybrid approach combining Ensemble Empirical Mode Decomposition (EEMD) and Long Short-Term Memory (LSTM) deep learning was utilized. Similarly, one could consider applying the obtained results by directly employing machine learning techniques,as recently proposed by [38], to construct a global model for TEC using Global Ionospheric Maps data along with features such as geomagnetic and solar activity indexes. Conceptualization, P.D.M. and T.A. ; methodology, G.L. and T.A. ; formal analysis, G.L. ; investigation, P.D.M., G.L., T.A. and G.C. ; data curation, G.L. ; writing--original draft preparation, P.D.M. and G.L. ; writing--review and editing, all authors. All authors have read and agreed to the published version of the manuscript. T.A. received funding from the \"Bando per il finanziamento di progetti di Ricerca Fondamentale 2022\" mini-grant of the Italian National Institute for Astrophysics (INAF) for \"The predictable chaos of space weather events\". Swarm satellite data can be accessed at [[http://earth.esa.int/swarm](http://earth.esa.int/swarm)]([http://earth.esa.int/swarm](http://earth.esa.int/swarm)), accessed on 15 January 2022. SuperMAG data are available at [[https://supermag.jhuapl.edu/](https://supermag.jhuapl.edu/)]([https://supermag.jhuapl.edu/](https://supermag.jhuapl.edu/)), accessed on 18 April 2023. IMF components and solar wind speed data are freely available at [[https://cdaweb.gsfc.nasa.gov/index.html/](https://cdaweb.gsfc.nasa.gov/index.html/)]([https://cdaweb.gsfc.nasa.gov/index.html/](https://cdaweb.gsfc.nasa.gov/index.html/)), accessed on 2 November 2022. The results presented herein rely on data collected by the ESA's Swarm mission. We thank the European Space Agency that supports the Swarm mission. We gratefully acknowledge the SuperMAG collaborators ([[https://supermag.jhuapl.edu/info/?page=acknowledgement](https://supermag.jhuapl.edu/info/?page=acknowledgement)]([https://supermag.jhuapl.edu/info/?page=acknowledgement](https://supermag.jhuapl.edu/info/?page=acknowledgement)), accessed on 18 April 2023). The IMF components and solar wind velocity data were obtained from the OMNIWeb Data Explorer website, which is operated by the Goddard Space Flight Center (NASA) Space Physics Data Facility, for which we are grateful. In addition, we acknowledge the national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, South Africa, UK, and USA that funded the SuperDARN radar network. G.L. acknowledges the PhD course in Astronomy, Astrophysics, and Space Science of the University of Rome \"Sapienza\", University of Rome \"Tor Vergata\", and Istituto Nazionale di Geofisica e Vulcanologia, Italy. The authors declare no conflicts of interest.