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- Robert W. Schunk
- Center for Atmospheric and Space Sciences Utah State University Logan Utah USA
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- Ludger Scherliess
- Center for Atmospheric and Space Sciences Utah State University Logan Utah USA
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- Jan J. Sojka
- Center for Atmospheric and Space Sciences Utah State University Logan Utah USA
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- Donald C. Thompson
- Center for Atmospheric and Space Sciences Utah State University Logan Utah USA
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- David N. Anderson
- NOAA/Space Environment Center Department of Commerce Boulder Colorado USA
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- Mihail Codrescu
- NOAA/Space Environment Center Department of Commerce Boulder Colorado USA
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- Cliff Minter
- NOAA/Space Environment Center Department of Commerce Boulder Colorado USA
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- Timothy J. Fuller‐Rowell
- NOAA/Space Environment Center Department of Commerce Boulder Colorado USA
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- Roderick A. Heelis
- W. B. Hanson Center for Space Sciences University of Texas at Dallas Richardson Texas USA
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- Marc Hairston
- W. B. Hanson Center for Space Sciences University of Texas at Dallas Richardson Texas USA
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- Bruce M. Howe
- Applied Physics Laboratory University of Washington Seattle Washington USA
書誌事項
- 公開日
- 2004-01-31
- 権利情報
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- http://onlinelibrary.wiley.com/termsAndConditions#vor
- DOI
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- 10.1029/2002rs002794
- 公開者
- American Geophysical Union (AGU)
この論文をさがす
説明
<jats:p>The ionosphere is a highly dynamic medium that exhibits weather disturbances at all latitudes, longitudes, and altitudes, and these disturbances can have detrimental effects on both military and civilian systems. In an effort to mitigate the adverse effects, we are developing a physics‐based data assimilation model of the ionosphere and neutral atmosphere called the Global Assimilation of Ionospheric Measurements (GAIM). GAIM will use a physics‐based ionosphere‐plasmasphere model and a Kalman filter as a basis for assimilating a diverse set of real‐time (or near real‐time) measurements. Some of the data to be assimilated include in situ density measurements from satellites, ionosonde electron density profiles, occultation data, ground‐based GPS total electron contents (TECs), two‐dimensional ionospheric density distributions from tomography chains, and line‐of‐sight UV emissions from selected satellites. When completed, GAIM will provide specifications and forecasts on a spatial grid that can be global, regional, or local. The primary output of GAIM will be a continuous reconstruction of the three‐dimensional electron density distribution from 90 km to geosynchronous altitude (35,000 km). GAIM also outputs auxiliary parameters, including <jats:italic>N</jats:italic><jats:sub><jats:italic>m</jats:italic></jats:sub><jats:italic>F</jats:italic><jats:sub>2</jats:sub>, <jats:italic>h</jats:italic><jats:sub><jats:italic>m</jats:italic></jats:sub><jats:italic>F</jats:italic><jats:sub>2</jats:sub>, N<jats:sub>m</jats:sub>E, h<jats:sub>m</jats:sub>E, and slant and vertical TEC. Furthermore, GAIM provides global distributions for the ionospheric drivers (neutral winds and densities, magnetospheric and equatorial electric fields, and electron precipitation patterns). In its specification mode, GAIM yields quantitative estimates for the accuracy of the reconstructed ionospheric densities.</jats:p>
収録刊行物
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- Radio Science
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Radio Science 39 (1), Artn Rs1s02-, 2004-01-31
American Geophysical Union (AGU)

