Projects per year
Abstract
Ionospheric storms can have important effects on radio communications and navigation systems. Storm time ionospheric predictions have the potential to form part of effective mitigation strategies to these problems. Ionospheric storms are caused by strong forcing from the solar wind. Electron density enhancements are driven by penetration electric fields, as well as by thermosphere-ionosphere behavior including Traveling Atmospheric Disturbances and Traveling Ionospheric Disturbances and changes to the neutral composition. This study assesses the effect on 1 h predictions of specifying initial ionospheric and thermospheric conditions using total electron content (TEC) observations under a fixed set of solar and high-latitude drivers. Prediction performance is assessed against TEC observations, incoherent scatter radar, and in situ electron density observations. Corotated TEC data provide a benchmark of forecast accuracy. The primary case study is the storm of 10 September 2005, while the anomalous storm of 21 January 2005 provides a secondary comparison. The study uses an ensemble Kalman filter constructed with the Data Assimilation Research Testbed and the Thermosphere Ionosphere Electrodynamics General Circulation Model. Maps of preprocessed, verticalized GPS TEC are assimilated, while high-latitude specifications from the Assimilative Mapping of Ionospheric Electrodynamics and solar flux observations from the Solar Extreme Ultraviolet Experiment are used to drive the model. The filter adjusts ionospheric and thermospheric parameters, making use of time-evolving covariance estimates. The approach is effective in correcting model biases but does not capture all the behavior of the storms. In particular, a ridge-like enhancement over the continental USA is not predicted, indicating the importance of predicting storm time electric field behavior to the problem of ionospheric forecasting.
Original language | English |
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Pages (from-to) | 764-778 |
Number of pages | 15 |
Journal | Journal of Geophysical Research: Space Physics |
Volume | 121 |
Issue number | 1 |
Early online date | 25 Jan 2016 |
DOIs | |
Publication status | Published - 18 Feb 2016 |
Keywords
- assimilation
- composition
- forecasting
- Ionosphere
- storms
- thermosphere
Fingerprint
Dive into the research topics of 'Ionospheric data assimilation and forecasting during storms'. Together they form a unique fingerprint.Projects
- 1 Finished
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KE Fellowship - Maximising Impact from Ionospheric Research
Natural Environment Research Council
1/09/16 → 31/08/20
Project: Research council
Profiles
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Cathryn Mitchell
- Department of Electronic & Electrical Engineering - Professor
- Centre for Digital, Manufacturing & Design (dMaDe)
- Centre for Climate Adaptation & Environment Research (CAER)
- Institute for Advanced Automotive Propulsion Systems (IAAPS)
Person: Research & Teaching, Core staff, Affiliate staff