1. 1. S. Datta-Barua, Illinois Institute of Technology D. Miladinovich, Illinois Institute of Technology G. Bust, John Hopkins University Applied Physics Laboratory J. Makela, University of Illinois at Urbana-Champaign URSI AT-RASC May 18th 22nd 2015 Gran Canaria
2. 2. Special Thanks: John Meriwether, for instrumentation and data Funding Support by: NSF - AGS-1329383 NSF - AGS-1352602 2
3. 3. Motivation: improved estimation of ionosphere and thermosphere states (i.e., ion drift velocity, neutral wind velocity, etc.) Algorithm Update: Assimilation of neutral wind measurements for the first time 3
4. 4. The Ionosphere and Thermosphere (I.T.): 4 Figure. [1] Relationship of the atmosphere and ionosphere
5. 5. Solar Storm Ionosphere ThermosphereDuring Ionospheric storms the layers interact dynamically to redistribute plasma in the ionosphere One coupling mechanism with ionospheric plasma is through collisional drag with neutral winds of the thermosphere 5
6. 6. Ion continuity equation model: = + - ion velocity parallel to magnetic field lines = + g + D - neutral wind term = + + g + D 6
7. 7. Each term can be obtained either from a: measurement: or from a model: = , the difference between a measurement and model An over determined linear system can be formed We are motivated by the idea that more measurements may improve estimation. 7 = + + g + D gravity diffusion neutral wind field perpendicular wind loss production Electron density per time
8. 8. E.M.P.I.R.E. Estimating Model Parameters from Ionospheric Reverse Engineering Solves the linear system: = + + = + + [] = ; = + noise It is a Kalman filter! 8
9. 9. Global Navigation Satellite System (GNSS) Total Electron Content (TEC) Measurements [left] Fabry-Perot Interferometers (FPI) [right] 9 Figure [2] Slant Total Electron Content Figure [3] FPI at ESRANGE, Kiruna Sweden
10. 10. Ionospheric Data Assimilation 4 Dimensional (IDA4D) estimates electron density measurement values at specified grid points. These measurements are finite differenced to obtain and placed into the measurement terms (i.e., ) 10
11. 11. Measures the Doppler shift of 2 + recombination emissions (630nm) to obtain neutral wind velocities. These velocities provide the line of sight neutral winds ... winds. We rotate them using the inclination and declination angles at the measurement point to produce 11 Figure [4] FPI On a Shed
12. 12. 12 TEC FPI Measurements, Models, HWM Weimer IGRF = + Kalman Filter (, , , ) + Results: Adjusted Models
13. 13. Date: October 25th 2011 Where: South East United States What: An ionospheric TEC enhancement lingers on Earths night side during the main phase of an ionospheric storm The Pisgah Astronomical Research Institute FPI Three different results: 1) No FPI Measurements 2) South and East Measurements 3) All Four Measurements 13 Ingested
14. 14. No FPI assimilation 14
15. 15. Half FPI Assimilation 15
16. 16. Full FPI Assimilation 16
17. 17. 17
18. 18. FPI measurements were assimilated for the first time to study neutral winds in the ionosphere Reduced RMS difference in neutral wind estimation at the location of ingestion Suggests that there is an overall improvement of measurements near the FPI ingestion point. 18 0 50 100 150 200 250 300 No Ingestion Half Ingestion RMS North West Ingested
19. 19. 2D maps of horizontal winds in the enhanced TEC region along with covariance analysis Assimilation of more FPI instruments in this region. 19
20. 20. Images [1] Relationship of the atmosphere and ionosphere http://en.wikipedia.org/wiki/Ionosphere [2] Slant Total Electron Content http://gnss.be/ionosphere_tutorial.php [3] FPI at ESRANGE, Kiruna Sweden https://www.ucl.ac.uk/star/research/planets/terrestrial/ observation [4] FPI On a Shed http://csl.illinois.edu/news/near- space-study-helping-predict-storms 20