Statistics – Applications
Scientific paper
Dec 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009agufmsa34a..02s&link_type=abstract
American Geophysical Union, Fall Meeting 2009, abstract #SA34A-02
Statistics
Applications
[2447] Ionosphere / Modeling And Forecasting, [7924] Space Weather / Forecasting, [7959] Space Weather / Models
Scientific paper
There are many empirical, physics-based, and data assimilation models that can probably be used for space weather applications and the models cover the entire domain from the surface of the Sun to the Earth’s surface. At Utah State University we developed two physics-based data assimilation models of the terrestrial ionosphere as part of a program called Global Assimilation of Ionospheric Measurements (GAIM). One of the data assimilation models is now in operational use at the Air Force Weather Agency (AFWA) in Omaha, Nebraska. This model is a Gauss-Markov Kalman Filter (GAIM-GM) model, and it uses a physics-based model of the ionosphere and a Kalman filter as a basis for assimilating a diverse set of real-time (or near real-time) measurements. The physics-based model is the Ionosphere Forecast Model (IFM), which is global and covers the E-region, F-region, and topside ionosphere from 90 to 1400 km. It takes account of five ion species (NO+, O2+, N2+, O+, H+), but the main output of the model is a 3-dimensional electron density distribution at user specified times. The second data assimilation model uses a physics-based Ionosphere-Plasmasphere Model (IPM) and an ensemble Kalman filter technique as a basis for assimilating a diverse set of real-time (or near real-time) measurements. This Full Physics model (GAIM-FP) is global, covers the altitude range from 90 to 30,000 km, includes six ions (NO+, O2+, N2+, O+, H+, He+), and calculates the self-consistent ionospheric drivers (electric fields and neutral winds). The GAIM-FP model is scheduled for delivery in 2012. Both of these GAIM models assimilate bottom-side Ne profiles from a variable number of ionosondes, slant TEC from a variable number of ground GPS/TEC stations, in situ Ne from four DMSP satellites, line-of-sight UV emissions measured by satellites, and occultation data. Quality control algorithms for all of the data types are provided as an integral part of the GAIM models and these models take account of latent data (up to 3 hours). The trials, tribulations and rewards of constructing and maintaining operational data assimilation models will be discussed.
Scherliess Ludger
Schunk Robert W.
Sojka Jan J.
Thompson Daniel C.
Zhu Lijun
No associations
LandOfFree
Operational Space Weather Models: Trials, Tribulations and Rewards does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Operational Space Weather Models: Trials, Tribulations and Rewards, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Operational Space Weather Models: Trials, Tribulations and Rewards will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1780369