| NSF Org: |
AGS Division of Atmospheric and Geospace Sciences |
| Recipient: |
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| Initial Amendment Date: | July 27, 2004 |
| Latest Amendment Date: | May 7, 2007 |
| Award Number: | 0417666 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Cassandra G. Fesen
AGS Division of Atmospheric and Geospace Sciences GEO Directorate for Geosciences |
| Start Date: | August 1, 2004 |
| End Date: | April 30, 2008 (Estimated) |
| Total Intended Award Amount: | $0.00 |
| Total Awarded Amount to Date: | $106,372.00 |
| Funds Obligated to Date: |
FY 2005 = $25,988.00 FY 2006 = $7,980.00 FY 2007 = $0.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
1100 WILSON BLVD ARLINGTON VA US 22209-2249 (301)883-4003 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
1100 WILSON BLVD ARLINGTON VA US 22209-2249 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | AERONOMY |
| Primary Program Source: |
app-0105 app-0106 app-0107 01000809DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.050 |
ABSTRACT
A collaboration between mathematical and space scientists provides a novel data assimilation algorithm, capable of handling temporally and spatially inhomogeneous data sets, to assemble (in a model-useful format) an extensive amount of total electron content (TEC) data. These data are assembled from ionosonde networks, GPS receiver networks, satellite electron density measurements, radio occultation data, and other sources. The data are then described in a multi-resolution ionosphere model using spherical wavelet functions, and a regional description of the ionosphere in the equatorial anomaly is a primary focus of the model application. The methodology takes resultant ionospheric multi-dimensional regional ionospheric maps, generated by the data assimilation and the wavelet description, and then updates the International Reference Ionosphere (IRI) model for improved global ionospheric model accuracy. The research expects to significantly improve operational predictive capability.
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