Ionospheric/Thermospheric Variability At Middle Latitudes Obtained From The Global Assimilation Of Ionospheric Measurements (GAIM) Model

Details Ionospheric/Thermospheric Variability At Middle Latitudes Obtained From The Global Assimilation Of Ionospheric Measurements (GAIM) Model Ionospheric/Thermospheric Variability At Middle Latitudes Obtained From The Global Assimilation Of Ionospheric Measurements (GAIM) Model

Dec 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006agufmsa12a..03s&link_type=abstract

American Geophysical Union, Fall Meeting 2006, abstract #SA12A-03

Physics

2427 Ionosphere/Atmosphere Interactions (0335), 2437 Ionospheric Dynamics, 2443 Midlatitude Ionosphere, 2447 Modeling And Forecasting

Scientific paper

It is well known that the thermosphere/ionosphere system at middle latitudes is strongly coupled, and therefore, a study of mid-latitude thermospheric variability must include the ionosphere. Variations in the ionospheric plasma dynamics and distribution are strongly driven by changes in the thermospheric winds and composition, and consequently, the ionosphere is a sensitive indicator for thermospheric variability. In particular, ionospheric observations can be used to obtain information about the corresponding changes in the thermosphere. This is in particular important because thermospheric observations are sparse and very limited in their spatial and temporal coverage and unobserved over large parts of the globe. As shown by meteorologists and oceanographers, a powerful way to obtain these unobserved parameters is with the use of data assimilation models. At USU, we have developed two GAIM data assimilation models with different complexity and both provide global and regional specifications of the 3-dimensional ionosphere plasma dynamics. One of these models is our Full Physics-Based Kalman filter data assimilation model, which is based on a physics-based model for the ionosphere-plasmasphere system, a diverse array of data sources, and an ensemble Kalman filter data assimilation technique. This model covers the ionosphere-plasmasphere system from 90 - 30,000 km altitude and includes 6 ion species (NO+, N_2+, O_2+, O+, He+, H+) and needs to be run on a cluster of ~30 CPU workstations. The strength of this model is that in addition to the global and regional 3-D ionosphere electron density distribution it also self- consistently determines the corresponding ionospheric drivers, including the thermospheric neutral winds and composition and the electric fields. The model can assimilate a variety of different data types, including GPS/TEC from up to 1000 ground receivers, in situ N_e from several DMSP satellites, and bottomside N_e profiles from 30 digisondes. We have used this model to study the variability of the mid-latitude ionosphere/thermosphere system over the American sector, where ground-based ionospheric observations are abundant. The model was used on a case-by-case basis to determine the various thermospheric driving forces and to study their temporal and spatial variability. We will present examples of the ionospheric and thermospheric variability obtained from our model runs and compare the results with independent data.

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