Graph
The root-mean squared error (RMSE) of atomic oxygen ion density over the globe is reduced compared to the control simulation when neutral and ionospheric quantities are assimilated as in OSSI5. The atomic oxygen ion density (an ionospheric quantity) can be significantly reduced by assimilating neutral parameters as in OSSI1 and OSSI2 showing that the ionosphere and thermosphere are closely coupled. (OSS1 – assimilates neutral temperature, OSSI2 like OSSI1 + horizontal wind, atomic and molecular oxygen density, OSSI3 atomic oxygen ion density, OSSE4 like OSSE3 + electron and ion temperatures, OSSI5 all of the above) Credit: Hsu et al. [2024], Figure 8
Editors’ Highlights are summaries of recent papers by AGU’s journal editors.
Source: Earth and Space Science

Our society relies heavily on space assets which are susceptible to space weather effects. Space, here focused on the ionosphere-thermosphere (IT), is sparsely sampled, and IT models are therefore important to predict the space environment. NASA’s Global Dynamic Constellation (GDC) will provide necessary observations to understand better how our IT system responds to solar and magnetospheric forcing causing space weather.

Hsu et al. [2024] examine the impact of assimilating GDC observations in a numerical IT model on the accuracy of the prediction. The prediction is most accurate when ionospheric and thermospheric observations are used in the assimilation system. The study emphasizes the need for concurrent ionosphere and thermosphere observations, like GDC will provide, to improve IT prediction of space weather.  

Citation: Hsu, C.-T., Matsuo, T., Kershaw, H., Dietrich, N., Smith, M., Anderson, J., et al. (2024). A community Ionosphere-Thermosphere Observing System Simulation Experiment (OSSE) tool: Geospace Dynamics Constellation example. Earth and Space Science, 11, e2024EA003684. https://doi.org/10.1029/2024EA003684  

—Astrid Maute, Editor, Earth and Space Science

Text © 2024. The authors. CC BY-NC-ND 3.0
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