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Fuller-Rowell et al. 2006
Fuller-Rowell, T., Araujo-Pradere, E., Minter, C., Codrescu, M., Spencer, P., Robertson, D. and Jacobson, A.R. (2006). US-TEC: A new data assimilation product from the Space Environment Center characterizing the ionospheric total electron content using real-time GPS data. Radio Science 41: doi: 10.1029/2005RS003393. issn: 0048-6604.

The potential of data assimilation for operational numerical weather forecasting has been appreciated for many years. For space weather it is a new path that we are just beginning to explore. With the emergence of satellite constellations and the networks of ground-based observations, sufficient data sources are now available to make the application of data assimilation techniques a viable option. The first space weather product at Space Environment Center (SEC) utilizing data assimilation techniques, US-TEC, was launched as a test operational product in November 2004. US-TEC characterizes the ionospheric total electron content (TEC) over the continental United States (CONUS) every 15 min with about a 15-min latency. US-TEC is based on a Kalman filter data assimilation scheme driven by a ground-based network of real-time GPS stations. The product includes a map of the vertical TEC, an estimate of the uncertainty in the map, and the departure of the TEC from a 10-day average at that particular universal time. In addition, data files are provided for vertical TEC and the line-of-sight electron content to all GPS satellites in view over the CONUS at that time. The information can be used to improve single-frequency GPS positioning by providing more accurate corrections for the ionospheric signal delay, or it can be used to initialize rapid integer ambiguity resolution schemes for dual-frequency GPS systems. Validation of US-TEC indicates an accuracy of the line-of-sight electron content of between 2 and 3 TEC units (1 TECU = 1016 el m-2), equivalent to less than 50 cm signal delay at L1 frequencies, which promises value for GPS users. This is the first step along a path that will likely lead to major improvement in space weather forecasting, paralleling the advances achieved in meteorological weather forecasting.

BACKGROUND DATA FILES

Abstract

Keywords
Ionosphere, Midlatitude ionosphere, Ionosphere, Modeling and forecasting, Atmospheric Processes, Data assimilation, Radio Science, Ionospheric physics (1240, 2400), Space Weather, Models
Journal
Radio Science
Publisher
American Geophysical Union
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