TitleGlobal Assimilation of Ionospheric Measurements (GAIM) - Gauss Markov (GM) Model: Improved Specifications with Multiple Data Types
Publication TypeJournal Article
Year of Publication2014
AuthorsGardner, LC, Schunk, RW, Scherliess, L, Sojka, JJ, Zhu, L
JournalSpace Weather
Date Published11/2014
KeywordsData Assimilation, Ionosphere, Modeling

The Earth's ionosphere is a highly dynamic region that is almost constantly in a state of flux. Solar radiation, geomagnetic activity, chemical reactions, and natural dynamics all act to perturb the state of the ionosphere. The ionosphere changes on time scales of hours to days, with the fine-scale ionospheric structures that are frequently observed lacking in global physics-based models due to time-step and spatial resolution constraints. To properly specify the ionosphere, data is needed, thus data assimilation. The Utah State University GAIM-GM model uses a data assimilation method to correct a physics-based model of the ionosphere using 5 different data types, divided into 9 different data sources. Multiple data types are necessary because the data from any individual data source will not be sufficient for global reconstructions. The GAIM-GM specification (in real-time) can then be used to correct for ionospheric propagation delays, thereby improving geo-location and communications. The focus here is to show the quantitative effects that multiple data types have on GAIM-GM ionospheric specifications for a relatively quiet day (April 19) in 2012.

Short TitleSpace Weather

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