Accurately Mapping Earth's Ionospheric Electron Density Using 4D-Var Data Assimilation

What is it about?

The problem: why we need better maps The ionosphere is important because it contains electrically charged particles (electrons), which significantly affect satellite signals, including those used by the Global Navigation Satellite System (GNSS), such as GPS. If the ionosphere becomes unstable, for example during a geomagnetic storm, these signals can become distorted, resulting in errors in navigation and positioning. In order to minimise these errors and improve systems like GPS, scientists require a method of creating reliable three-dimensional snapshots of electron density in this vast region. This paper addresses this challenge by presenting a new data assimilation scheme called the Neustrelitz Electron Density Assimilation Model (NEDAM). NEDAM is based on a technique called four-dimensional variational assimilation (4D-Var). This is how it works: 1. Background 'Climate': It starts with a base layer of knowledge in the form of the Neustrelitz Electron Density Model (NEDM), which predicts the long-term average 'climatological' behaviour of the ionosphere. 2. Real-time 'weather': The NEDAM then integrates fresh, real-time measurements from thousands of GNSS satellites (observations of total electron content, or TEC). 3. Refinement: The assimilation scheme combines historical climate data with momentary satellite data to generate a much more accurate 4D picture (three dimensions of space plus time), capturing short-term weather variations. 4. Advanced accuracy: Crucially, the model incorporates advanced mathematical handling of observational errors. It recognises that satellite signals close to each other are often correlated due to geometry. This results in a more accurate final map. Key Results and Validation The model’s performance was rigorously tested using data collected during the severe space weather event of the September 2017 geomagnetic storm. Storm Performance: NEDAM proved to be much more accurate than the background model (NEDM) at predicting ionospheric disturbances when compared against measurements from ground-based radar instruments (ionosondes), and even outperformed a respected physics-based model (the TIE-GCM). For instance, measuring the critical frequency of the F2 layer became significantly more accurate, with the root mean square error (RMSE) dropping by up to 0.54 MHz at one station. Vertical Mapping Success: A major difficulty in ionospheric mapping is accurately determining the height of the electron density peak (hmF2) using only ground-based satellite observations. However, when NEDAM's results were compared with independent satellite profiles from COSMIC-1 radio occultation, it successfully reconstructed both the peak density and the peak density height. This is a capability lacking in previous research. Future Impact: The advanced methodology developed through NEDAM is designed to provide crucial services for space weather monitoring, GPS positioning and navigation in near real-time, while deepening our understanding of how the ionosphere moves and changes.

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Photo by Robynne Hu on Unsplash

Photo by Robynne Hu on Unsplash

Why is it important?

The development of the Neustrelitz Electron Density Assimilation Model (NEDAM) is both unique and timely, as it improves the accuracy of ionospheric mapping, particularly during critical space weather events. Its implementation of a four-dimensional variational assimilation scheme (4D-Var), combined with improvements in how errors are handled, sets it apart. Unlike previous assimilation techniques, which often assumed that observations were independent, NEDAM improves observation covariance by considering signal geometry. This is more appropriate when signals are correlated or intersect during disturbed periods. Furthermore, NEDAM handles background covariance using a Gaussian-Markov random field approximation. This approach substantially improves the reconstruction of the vertical structure of the ionosphere. Previous research that used only ground-based GNSS Total Electron Content (TEC) observations found it difficult to accurately determine the peak density height (hmF2). However, when validated against COSMIC-1 radio occultation data, NEDAM was found to accurately reconstruct both the peak density and the peak density height. This was validated during the intense geomagnetic storm period in September 2017. During this storm, NEDAM's accuracy in predicting the F2-layer critical frequency (foF2) was demonstrably superior to that of the background model (NEDM), improving the Root Mean Square Error (RMSE) by up to 0.54 MHz, and outperforming the well-established physics-based model TIE-GCM. This improved accuracy is vital for applications such as near-real-time space weather monitoring, GPS positioning and navigation, and enhancing the general understanding of ionospheric dynamics.

Perspectives