1. Total Electron Content 32N 115W, 2007-2009 Rachel Thessin, CSI 763, April 15, 2010

2. Data Overview  US TEC data from the National Geophysical Data Center  Two data types:  Ground GPS: CORS, RTIGS  Sat GPS: GPS/Met  Vertical TEC grids  1 deg x 1 deg  15 min resolution  Oct 2004 – present  Each day: 26 MB compressed; 64 MB uncompressed http://www.ngdc.noaa.gov/stp/IONO/USTEC/  TEC: total electron content (integral of electron density)

3. Time Series  Extracted TEC 2007-2009 at 32N 115W  Overlaps with 12/2009 5.8 mag earthquake

4. Data Expectations  TEC is a function of  Solar / geomagnetic activity  Time of day  Day of year (season)  Lat / Lon / Alt  2007 – 2009: Solar minimum  Relatively flat solar activity across three years http://solarscience.msfc.nasa.gov/images/ssn_predict_l.gif

5. Literature Review, 1 of 2  Dautermann et al ("Investigation of ionospheric electron content variations before earthquakes in southern California, 2003 – 2004," Journal of Geophysical Research, VOL. 112, 2007)  11 year, 1 year, 27 day, 1 day, 12 hr

6. Literature Review, 2 of 2  Bilitza (2001)  “International Reference Ionosphere 2000,” Radio Science, v. 36, n. 2, pp 261-275, March-April 2001 “International Reference Ionosphere 2000,” Radio Science, v. 36, n. 2, pp 261-275, March-April 2001  E region  Solar influenced  24-hr periodicity related to SZA  F region  plasma is transported along magnetic field lines  24-hr dependence related to LT  External drivers  solar irradiance (11-year cycle) (and hence the use of F10.7 and twelve- month running mean of SSN as inputs)  Conclusion: IRI will miss the 27-day periodicity in the data  These periodicities are ephemeral and caused by “random” events.

7. Time Series  2007-2009 at 32N 115W  Flat with daily varaitions

8. Data Gaps  120 gaps among 103,000 data points  18 1-minute gaps and 112 gaps longer than 16 minutes  Linear Interpolation

9. Data Distribution  TEC varies daily  Sinuosoidal appearance  Most data values at peak or trough  bimodal data distribution  Bounded on lower end, unbounded on upper end  broader upper peak

10. Autocorrelation  Long correlation lag  Values correlated with counterparts one year later  Yearly cycle + flat solar activity  Short correlation lag  Large variance in correlation small lags apart  Daily variation in TEC

11. Raw Periodogram  Signal at period of 1 day; no other signals  Aliasing of this signal  Data set is too short and flat to see 1-year, 11-year signals  12-hour – 1/(1/2 day) = 2 day -1 ; 27-day – 1/(27 days) = 0.037 day -1  1-year – 1/(365 days) = 0.0027 day -1

12. Welchs Periodogram  8 equal-sized, overlapping windows with a Hamming function shape leads to less high-freq noiseHamming function shape  1-day and 12-hr signals visible

13. Welch’s Periodogram, 60-day window  Smaller window  less high-freq noise  12 hr signal becomes more visible

14. Welch’s Periodogram, 10-day window  Smaller window  less high-freq noise  12 hr signal becomes more visible  No longer physically feasible to see 1 year or 27 day signals

15. Error on Periodogram  Bootstrap, n = 1000, l = 45 days  Peak at 1 day is statistically significant, as is peak at 12 hours  Aliasing peaks seem almost significant – meaning of 3 hour period?

16. Error on Welch’s  Bootstrap, n=1000, l = 45 days  1 day and 12 hour signals statistically significant