Datta-Barua, URSI AT-RASC, 2015, Canary Islands, Ionospheric-Thermospheric State Estimation With...
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Ionospheric- Thermospheric State Estimation With Neutral Wind Data Assimilation 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 18 th – 22 nd 2015 Gran Canaria
Datta-Barua, URSI AT-RASC, 2015, Canary Islands, Ionospheric-Thermospheric State Estimation With Neutral Wind Data Assimilation V3
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. Special Thanks: John Meriwether, for instrumentation and
data Funding Support by: NSF - AGS-1329383 NSF - AGS-1352602 2
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. The Ionosphere and Thermosphere (I.T.): 4 Figure. [1]
Relationship of the atmosphere and ionosphere
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. Ion continuity equation model: = + - ion velocity parallel
to magnetic field lines = + g + D - neutral wind term = + + g + D
6
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. 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. 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. 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. 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
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. No FPI assimilation 14
15. Half FPI Assimilation 15
16. Full FPI Assimilation 16
17. 17
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. 2D maps of horizontal winds in the enhanced TEC region
along with covariance analysis Assimilation of more FPI instruments
in this region. 19
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