Publication: Journal of Geophysical Research, Space Physics; First HAO Author: Nick Pedatella; Authors names listed in article: N. M. Pedatella, J. L. Anderson, C. H. Chen, K. Raeder, J. Liu, H.-L. Liu, and C.H. Lin
The Earth’s upper atmosphere impacts a wide range of technologies, including satellite communication and navigation signals. Specification and forecasting of the upper atmosphere are critical for mitigating these effects. Improved specification of the state of the upper atmosphere can also improve scientific understanding of this region.
Data assimilation, which statistically combines a background model with observations, has recently been adopted as a means to improve upper atmosphere specification and forecasting. However, data assimilation systems focused on the upper atmosphere typically have lower boundaries near 100 km, and they do not consider the variability in wave forcing that originates at lower altitudes. This represents a limitation due to the known importance of lower atmosphere forcing on the day-to-day variability of the ionosphere. The current study presents initial results of the assimilation of ionosphere observations in a whole atmosphere model that extends from the surface to ~500-700 km. The model is based on the Whole Atmosphere Community Climate Model with thermosphere-ionosphere eXtension (WACCMX) with data assimilation provided by the Data Assimilation Research Testbed (DART) ensemble Kalman filter. The results demonstrate the positive impact of assimilating ionosphere observations on both short-term forecasts and analysis fields. This represents the first demonstration of a data assimilation system capable of assimilating observations from throughout the entire atmosphere (0-500 km).