Lei’s new paper entitled “Assessment of Storm-time Ionospheric Electron Density Measurements from Spire Global CubeSat GNSS Radio Occultation Constellation” is out now in GPS Solutions

Lei’s new paper entitled “Concentric Traveling Ionospheric Disturbances (CTIDs) Triggered by the 2022 Tonga Volcanic Eruption” is out now in JGR-space physics

Lei submitted a paper to GPS Solutions last week. This study presents a comprehensive evaluation of storm-time ionospheric electron density measurements derived from Spire RO data by comparing them with measurements obtained from digisonde, incoherent scatter radar (ISR), and the constellation observing system for meteorology, ionosphere, and climate 2(COSMIC2) mission during February 2020 - December 2021. Results showed electron density profiles (EDP) retrieved from Spire data are in general agreement with those from digisonde, ISR, and COSMIC2 RO observations, although Spire RO-retrieved EDPs sometimes are noisier than others. Spire RO-derived F2 layer peak density (NmF2) and peak height (hmF2) agree well with collocated measurements from digisonde and COSMIC2. The good performance of Spire RO-derived ionospheric parameters suggests that low cost CubeSats can provide reliable ionospheric measurements to significantly contribute to global ionospheric monitoring.

Full manuscript can be accessed by emailing lei.liu@colorado.edu

Lei submitted a paper to IEEE TGRS today. The paper applies the convolutional long short-term memory (convLSTM)-based machine learning (ML) models to forecast global ionospheric total electron content (TEC) maps with up to 24 hours of lead time at a 1-hour interval.

Full manuscript can be accessed by request at lei.liu@colorado.edu

Lei’s new paper entitled Arctic TEC Mapping Using Integrated LEO-based GNSS-R and Ground-based GNSS Observations: A Simulation Study is out now in IEEE Transactions on Geoscience and Remote Sensing

Lei Liu is presenting a talk at 2021 AGU Fall meeting titled Machine learning-based Prediction of global TEC and High-latitude ROTI Maps. In this presentation, the convLSTM-based ML model is to tackle two different GNSS applications: prediction of global TEC maps and high-latitude ROTI maps. The ML model we developed could play an important role in warning for space weather and satellite navigation communities.

• Talk Slides

Lei Liu is presenting a short poster at 2021 AGU Fall meeting in session SA25C: Distributed Ionospheric Measurements and Heterogeneous-Data-Driven Physics-Based Simulations for the Auroral Ionosphere.

• Abstract
• Manuscript

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