Solar Wind Driven Autoregression Model for Ionospheric Short Term Forecast (SWIF)
Abstract
This report results from a contract tasking Ionospheric Group, Institute for Space Applications and Remote Sensing, as follows: The grantee will investigate the development of an end-to-end short-term (up to 24 hours ahead) ionospheric prediction service, SWIF, based on a fusion of two diverse techniques: (1) an autoregression forecasting algorithm capable for real time predictions and (2) an empirical model (STIM) for predicting the onset and for scaling ionospheric disturbances during geomagnetic storms based on the solar wind parameters. The service will be applied for Athens location, by utilizing Athens Digisonde observations. Moreover, the predictions of the new algorithm will be evaluated in terms of both real observations and GCAM predictions for various ionospheric conditions and possible limitations of each method will be determined. The comparative evaluation of ionospheric prediction methods based on techniques of different approach would provide significant progress towards the accurate specification and forecasting of the evolution of ionospheric irregularities over Europe, which has a major impact on defense interests. In summary, the objectives of this project are: 1. development of the SWIF model 2. evaluation of the performance of the SWIF model in comparison to the results of other ionospheric models 3. on line demonstration of the SWIF model performance.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2008
- Accession Number
- ADA525997
Entities
People
- Anna Belehaki