Ionospheric disturbances observed coincident with the 2006 and 2009 North Korean underground nuclear tests

Transcription

1 GEOPHYSICAL RESEARCH LETTERS, VOL. 39,, doi: /2011gl050428, 2012 Ionospheric disturbances observed coincident with the 2006 and 2009 North Korean underground nuclear tests Yu-Ming Yang, 1 James L. Garrison, 1 and See-Chen Lee 1 Received 5 December 2011; accepted 22 December 2011; published 27 January [1] Acoustic-Gravity Waves (AGWs) in the neutral atmosphere can induce disturbances in the ionosphere that are subsequently observable in trans-ionospheric Global Navigation Satellite System (GNSS) measurements. Disruptive events on the Earth s surface, such as earthquakes, tsunamis and large explosions are one source of these disturbances. In this study, we apply wavelet analysis to enhance a crosscorrelation technique for detecting the presence of ionospheric disturbances in dual frequency GNSS time series collected from the GEONET (Japan) during the North Korean Underground Nuclear Tests (UGTs) conducted on 9 October 2006 and 25 May Through use of the wavelet coherence analysis, we are able to find significant wave trains in the Integrated Electron Content (IEC) data collected from the network. Low frequency disturbances, with periods between 3 and 12 min and horizontal propagation speeds between 75 and 453 m/s were found coincident with both the 2006 and 2009 events. High frequency disturbances, with periods between 2 and 5 min and horizontal speeds between 297 and 1322 m/s were found only after the 2009 event. The disturbances extracted from these signals showed propagation speeds, directions, and times of arrival coincident with the reported geographic location and times of the UGTs. Citation: Yang, Y.-M., J. L. Garrison, and S.-C. Lee (2012), Ionospheric disturbances observed coincident with the 2006 and 2009 North Korean underground nuclear tests, Geophys. Res. Lett., 39,, doi: /2011gl Introduction [2] Substantial research on the mechanism of ionospheric disturbances induced by atmospheric acoustic-gravity waves (AGWs) has been conducted [e.g., Hines, 1960; Georges and Hooke, 1970; Hunsucker, 1982; Hocke and Schlegel, 1996]. AGWs from solid earth events have been shown to be strong enough to transfer energy from the ground/sea surface into the atmosphere which then propagates up to the F-region of the ionosphere [Artru et al., 2004; Mai and Kiang, 2009; Hickey et al., 2009]. [3] Nuclear explosions are known to produce ionospheric disturbances through this mechanism [Breitling et al., 1967; Blanc, 1984; Fitzgerald, 1994; Goldflam et al., 1984; Fitzgerald et al., 1993]. These disturbances are understood to be the ionospheric response to the radiated acoustic fields from the spall zone of the UGT [Rudenko and Uralov, 1995; 1 School of Aeronautics and Astronautics, Purdue University, West Lafayette, Indiana, USA. Copyright 2012 by the American Geophysical Union /12/2011GL Krasnov and Drobzheva, 2005]. Krasnov and Drobzheva [2005] developed a model for studying the temperature and ionospheric electron perturbations caused by a UGT. Calculations from this model showed good agreement with the experimental measurements using Doppler radio sounding of the ionosphere above several underground explosions at the Semipalatinsk Test Site of the former Soviet Union. [4] In contrast to the Doppler radio sounding techniques, GPS senses the integrated electron content (IEC) along its signal propagation path. Ionospheric disturbances caused by earthquakes [Ducic et al., 2003], mine blasts [Calais et al., 1998], tsunamis [Artru et al., 2005] and many other natural and anthropogenic sources have been observed in GPS network data. Signal processing methods for detecting these disturbances in IEC time series include spectral tests [Afraimovich et al., 2003], the Statistical Angle-of-Arrival and Doppler Method (SADM-GPS) [Afraimovich et al., 2000] and cross-correlation [Garrison et al., 2007; Hernández-Pajares et al., 2006]. All of these approaches assume that a single perturbation is observable at a time and that the disturbance can be approximated as a quasi-monochromatic wave. However, multiple perturbations may be present within the same time and space, as prior studies have shown that the occurrence rate of natural disturbances is quite high. Šauli et al. [2006] applied wavelet decomposition to ionosonde measurements of disturbances produced during a solar eclipse, demonstrating an improved ability to separate different wave structures. [5] North Korea is known to have conducted two UGTs, the first on 9 October 2006 and the second on 25 May The reported magnitude of the UGT in 2009 was larger than that in The reported location for the first and second tests were N, E and N, E, respectively. A recent study on ionospheric responses from the 2009 UGT event has conclude that a UGT-generated ionospheric disturbances propagate radially from the event with the relatively constant velocity of roughly 273 m/s, estimated from GNSS measurements of 7 stations in South Korea [Park et al., 2011]. However, the method used by Park et al. [2011] is not able to classify different types of disturbances that may be present in the same IEC time series, or to directly estimate the propagation speed and direction. [6] In this study, we applied wavelet analysis to identify time-frequency regions of high coherence, identifying the presence of a propagating disturbance in the GEONET GPS data collected during the week of each of the two reported UGTs. We then used this information to select the bandwidth of filters that were applied to the IEC time series. The filtered time series were then cross-correlated following the approach of Garrison et al. [2007] to estimate the speed and direction of propagation for each disturbance. Geometric 1of6

2 Figure 1. Illustrations of the wavelet coherence analysis of subarea 31 in GEONET. Plots present the wavelet coherence spectrum for a 5-day data centered on the date of the 2009 North Korea UGT event. The coherence analysis reveals a potential ionospheric perturbation with dominant frequencies in a band from Hz at time 1:03 UT (about 9 minutes after the reported time of the detonation). The black contour represents the significance at 5% level (i.e., 95% confidence p ffiffi interval in statistics). The two curves show the distributions of COI for the singularity at the edge drops by a factor 2 /f. Regions above these two curves ensure that the edge effects are insignificant. consistency between these measurements and the reported time and location of the UGT events suggest that AGWs produced from these explosions were the source of the observed ionospheric disturbances. 2. Data Processing [7] The Integrated Electron Content (IEC) is defined as the integral of electron density along the path of radio frequency propagation from the transmitter to the receiver. Z receiver IECðÞ¼ t n e ðl; tþdl: ð1þ satellite Time-variation arises both due to the relative motion of the transmitter and receiver and variations in the electron density. For a dual-frequency GNSS receiver, the IEC time series can be calculated using the method of Mannucci et al. [1993]. [8] The wavelet coherency function [Kumar and Foufoula-Georgiou, 1997] of two IEC time series IEC 1 (t) and IEC 2 (t) is defined as R 1;2 ða; bþ ¼ W 1ða; bþw2 ða; bþ jw 1 ða; bþjjw 2 ða; bþj W n (a,b) is the continuous wavelet transform (CWT) [Mallat, 1999] of the IEC time series, IEC n (t), observed by receiver n. Z W n ða; bþ ¼ IEC n ðþy t t b dt ð3þ a y is a wavelet function, a is the wavelet scale, and b is the localized time index. W 2 *(a,b) is the conjugate of W 2 (a,b). We chose the Morlet wavelet, defined as a complex exponential function (when p >5)y(t) =e ipt e t2 /2 where p (frequency parameter) adjusts the time and scale resolution. The Morlet wavelet has a special feature in that the wavelet scale is the ð2þ 2of6

3 Figure 2. Ionospheric disturbances detected in each subarea on 25 May 2009 and 9 October The magnitude of vectors are proportional to the speed of the disturbance, and centered at the location of maximum IEC variation in the ionosphere. inverse of frequency (i.e., f = 1/a). jw n (a,b)j is the scalogram used by Šauli et al. [2006]. R 2 1,2 (a,b) can take values from 0 to 1, with larger values indicating the presence, at time index b, of coherent structure, at scale a, in both signals. Due to the finite IEC time series used to calculate the CWT, the cone of influence (COI) is analyzed to ensure the identified high coherence spectrums are not in the regions of edge effects. For the significance test of wavelet coherence, a Monte-Carlo approach is applied to test the null hypothesis H 0 statistically by repeating many independent realizations of the IEC time series. A detection threshold l a at the significance level a with N multiple tests is defined as l a =1 a 1/(N 1). For more details regarding the significance test refer to Maraun and Kurths [2004]. A threshold of 0.58 was set on R 2 1,2 (a,b) to identify strong coherence structures above significance at 5% level which implies 95% confidence interval in statistics (see Figure 1). [9] A set of band-pass filters, tuned to the frequencies of highest coherence, were then applied to each time series, before masking only those time frames of high coherence (R 2 1,2 (a,b) > 0.58 in Figure 1). The cross-correlation method of Garrison et al. [2007] was then applied to the filtered and masked time series to estimate propagation speeds and directions of the corresponding disturbances. This technique was based on the assumptions of planar wave propagation, a locally flat earth and thin shell ionosphere at the height of the maximum electron content. Through dividing the full network into smaller sub-areas, the variation of propagation direction and speed over a large area can be observed while maintaining the assumption of a planar wave over each small sub-area. We divided the full GEONET network (1235 GPS stations) into 32 sub-areas (on an approximately 1 1 grid as shown in Figure 2 and ran the wavelet coherence analysis on small sets of GPS stations within each sub-area. [10] Threshold values for selecting cross-correlation pairs were determined by applying the process of Garrison et al. [2007] to each subarea. The height of a thin-shell ionosphere was set to 350 km, corresponding to the height of maximum electron density determined from the IRI model on the event dates ( ionospheric/iri/). 3. Observations and Analysis [11] In this section, we will summarize our discovery, through use of the methods described above, of ionospheric disturbances coincident with the first and second North Korean UGT. GEONET data were processed over a range of 5-day windows of data centered on the 2009 and the 2006 events. These 5-day windows were used to determine if any disturbances appeared multiple days, in order to confirm that the observed disturbances were not diurnal artifacts, appearing by chance at the time and place of the UGT. Other than the disturbances reported later, which we attribute to the UGTs, only two other disturbances were observed in either 5-day windows of data. Some ionospheric disturbances were observed on the east coast of Japan approximately 15 hours and 39 hours after the 2009 event. However, the geometry of their propagation vectors were not consistent with the disturbances attributed to the UGTs, described later. No disturbances, other than those attributed to the 9 Oct 2006 UGT, were observed in the 2006 data. We also checked for space and terrestrial weather events which could have occurred within hours of the observed disturbances, to reduce the likelihood of the coincident appearance of a disturbance from another source. The space weather records from Space Weather Prediction Center of the National Oceanographic and Atmospheric Administration (NOAA) ( did not indicate any sudden and severe weather events during the time windows. [12] Figure 1 shows wavelet coherency computed between stations 0433 and 1041 on each of the 5 days of data, centered on the 2009 test. This example shows observations of satellite PRN 24 collected in sub-area 31. A high wavelet coherency exists on the event date (May ) only. The region of high coherency lies within a frequency band between Hz, centered at 1:03H UT (approximate 9 minutes after the reported time of the detonation). These 3of6

4 Figure 3. Illustrations of four GNSS stations filtered IEC waveforms for a 5-day data centered on 25 May 2009, the date of the second North Korea UGT. findings were used to design a Butterworth band-pass filter that was applied to the IEC time series prior to the crosscorrelation method of Garrison et al. [2007]. Figure 3 presents an example of a filtered IEC waveform. The averaged signal to noise ratio (SNR) of these disturbance signals from the four stations in Figure 3 on the event day (Day 145) is 11.2 db. The averaged SNR is 2.6 db for the other four days. [13] After filtering, the amplitude of the disturbances were found to range up to 0.17 TEC unit. This represents approximately a 2.6 percent change in the background level (6.5 TEC unit). This result is consistent with the calculations and experimental observations from Doppler radio sounding measurements presented by Krasnov and Drobzheva [2005]. [14] We applied this approach to the IEC data from every satellite visible during a 5-day window centered on each event. For the 25 May 2009 event, we also observed longperiod (3 12 min) disturbances in data from PRN 18 and 21 from 7 and 6 different sub-areas, respectively. The estimated horizontal speeds of these disturbances ranged from 61 to 174 m/s, consistent with gravity waves. Next, we tested the geometric consistency of these observed disturbances with a source at the reported UGT location. We plotted the apparent propagation time (difference between the mean time of the peak IEC and the reported explosion time) against the greatcircle distance from the reported test location. Figure 4 shows these results, overlaid with the expected arrival times for a range of horizontal propagation speeds. A 15 min shift was included in the apparent propagation times to account for the propagation delay from the surface of the Earth to the ionosphere. This figure shows the the arrival times and propagation distances are consistent with a disturbance propagating with a mean horizontal speed within the range of those observed. [15] We observed some short-period (2 5 min) disturbances in the signal from PRN 24 as reported above, within 3 subareas. Similar short-period disturbances were observed in the data from PRN 29 in 2 subareas. The horizontal speeds of these disturbances were also generally higher than the speed of the long-period disturbances (up to 1322 m/s) and appeared between 7 and 19 min. after the reported UGT time. This suggests that these disturbances were the result of acoustic waves produced at the source. Figure 5 shows ray traces (solid lines) of the acoustic field calculated by integrating d ds 1 c dx i ds ¼ 1 ; x i c where x i =(x 1, x 3 ) represents the horizon distance and the altitude from the point source, s is the arc length of the ray path, and c is the sound speed dependent on altitude. Dashed lines represent the arrival times in 1 minute increments. The horizontal distances of these observed IPP locations for PRN Figure 4. Comparison of the travel times and great-circle distances of the observed long period disturbances on 25 May 2009 against predicted arrival times for propagation speeds between 75 and 275 m/s. (P18, S19) represents PRN18 and subarea 19 respectively, for example. The travel times are reduced by 15 mins to approximate the propagation time from ground to ionosphere. 4of6

5 Figure 5. Ray traces of acoustic fields from a point source on the surface with no atmospheric winds. The MSIS-E-90 atmosphere model is applied for generating the vertical profile of the speed of sound on 25 May The Locations of the ionospheric pierce point (IPP) of PRN 29 and 24 are shown at the time of detection of short-period disturbances. The observed time agrees with that predicted from the ray trace. 24 and 29(at the height 350 km of ionosphere) are 257 km and 756 km, respectively, from the reported UGT location, indicated on Figure 5 as the thick circles. This observed arrival times, reported earlier, are consistent with the ray trace calculations that predict: 7 and 15 mins vs. 9 and 18 mins, respectively. All of the disturbances coincident with the 2009 UGT are plotted as vectors on Figure 2. The length of each vector is scaled with the estimated horizontal speed. The satellite PRN and subarea number are indicated on each vector and the tail of each vector is placed at the location of maximum IEC variation. [16] For the 9 Oct 2006 event, only long-period (3 12 min) disturbances were observed. These disturbances were detected in IEC measurements from satellites PRN 16 and 23, within 3 sub-areas each. Horizontal speeds for these disturbances were also within the gravity-wave regime, between 135 and 453 m/s. Figure 2 shows the location, horizontal speed, and direction of each of the disturbances found for the 9 Oct 2006 UGT. 4. Summary [17] Traveling ionospheric disturbances were detected using measurements from a GNSS network at distances of more than 1000 km from the reported locations of the 2006 and 2009 North Korean UGT events. Observations of short period disturbances with a fast horizontal speed (up to 1322 m/s) were observed 7 18 minutes after the 2009 UGT. Other disturbances with long period ( sec) and slower propagation speeds ( m/s) were observed 1 2 hours after both the 2006 and 2009 explosions. Directions of these observed disturbances were consistent with a source at the reported UGT locations. [18] Additionally, we have demonstrated that the crosscorrelation method, enhanced with a wavelet analysis, can be applied to detect and identify different types of ionospheric disturbances, separated in time and frequency. Ionospheric sounding, using large networks of GNSS receivers already deployed, has the potential to be a new sensing technique for monitoring weapons development and verifying test treaty compliance, complementing the present use of seismic and infrasound methods. [19] Acknowledgments. Yu-Ming Yang was supported by a NASA Earth and Space Science Fellowship, grant number NNX09AN52H. James Garrison was supported by the 2008 ASEE Summer Faculty Fellowship Program (SFFP) at Hansom Air Force Base. [20] The Editor thanks two anonymous reviewers for their assistance in evaluating this paper. References Afraimovich, E., K. Palamartchouk, and N. Perevalova (2000), Statistical angle-of-arrival and Doppler method for GPS radio interferometry of TIDS, Adv. Space Res., 26(6), Afraimovich, E. L., N. P. Perevalova, and S. V. Voyeiko (2003), Traveling wave packets of total elevtron content disturbances as deduced from global GPS network data, J. Atmos. Sol. Terr. Phys., 65(11 13), Artru, J., T. Farges, and P. Lognonne (2004), Acoustic waves generated from seismic surface waves: Propagation properties determined from Doppler sounding observations and normal-mode modelling, Geophys. J. Int., 158(3), Artru, J., V. Ducic, H. Kanamori, P. Lognonné, and M. Murakami (2005), Ionospheric detection of gravity waves induced by tsunamis, Geophys. J. Int., 160(3), Blanc, E. (1984), Interaction of an acoustic wave of artificial origin with the ionosphere as observed by vertical HF sounding at total reflection levels, Radio Sci., 19, Breitling, W. J., R. A. Kupferman, and G. J. Gassmann (1967), Traveling ionospheric disturbances associated with nuclear detonations, J. Geophys. Res., 72(1), Calais, E., J. B. Minster, M. A. Hofton, and M. A. Hedlin (1998), Ionospheric signature of surface mine blasts from Global Positioning System measurements, Geophys. J. Int., 132(1), Ducic, V., J. Artru, and P. Lognonné (2003), Ionospheric remote sensing of the Denali Earthquake Rayleigh surface waves, Geophys. Res. Lett., 30(18), 1951, doi: /2003gl Fitzgerald, T. (1994), Ionospheric measurements for the non-proliferation experiment, in Proceedings of the Symposium on The Non-Proliferation 5of6

6 Experiment (NPE): Results and Implications for Test Ban Treaties, edited by M. D. Denny, pp. 8 23, U.S. Dep. of Energy, Washington, D. C. Fitzgerald, T., R. Carlos, and P. E. Argo (1993), Integrated verification experiment data collected as part of the Los Alamos National Laboratory s source region program, Tech. Rep. LAUR , Los Alamos Natl. Lab., Los Alamos, N. M. Garrison, J. L., S.-C. G. Lee, J. S. Haase, and E. Calais (2007), A method for detecting ionospheric disturbances and estimating their propagation speed and direction using a large GPS network, Radio Sci., 42, RS6011, doi: /2007rs Georges, T. M., and W. H. Hooke (1970), Wave-induced fluctuations in ionospheric electron content: A model indicating some observational biases, J. Geophys. Res., 75(31), Goldflam, R., G. McCartor, and B. Wortman (1984), Ionospheric gravity waves from nuclear surface bursts, Tech. Rep. MRC-R-825, Mission Res. Corp., Santa Barbara, Calif. Hernández-Pajares, M., J. M. Juan, and J. Sanz (2006), Medium-scale traveling ionospheric disturbances affecting GPS measurements: Spatial and temporal analysis, J. Geophys. Res., 111, A07S11, doi: / 2005JA Hickey, M. P., G. Schubert, and R. L. Walterscheid (2009), Propagation of tsunami-driven gravity waves into the thermosphere and ionosphere, J. Geophys. Res., 114, A08304, doi: /2009ja Hines, C. O. (1960), Internal atmospheric gravity waves at ionospheric heights, Can. J. Phys., 38, Hocke, K., and K. Schlegel (1996), A review of atmospheric gravity waves and travelling ionospheric disturbances: , Ann. Geophys., 14(9), Hunsucker, R. (1982), Atmospheric gravity waves generated in the highlatitude ionosphere: A review, Rev. Geophys., 20(2), Krasnov, V., and Y. Drobzheva (2005), The acoustic field in the ionosphere caused by an underground nuclear explosion, J. Atmos. Sol. Terr. Phys., 67(10), Kumar, P., and E. Foufoula-Georgiou (1997), Wavelet analysis for geophysical applications, Rev. Geophys., 35(4), Mai, C.-L., and J.-F. Kiang (2009), Modeling of ionospheric perturbation by 2004 Sumatra tsunami, Radio Sci., 44, RS3011, doi: / 2008RS Mallat, S. (1999), A Wavelet Tour of Signal Processing, Academic, San Diego, Calif. Mannucci, A. J., B. D. Wilson, and C. D. Edwards (1993), A new method for monitoring the Earth s ionospheric total electron content using GPS global network, paper presented at Conference GPS-93, Inst. of Navig., Salt Lake City, Utah. Maraun, D., and J. Kurths (2004), Cross wavelet analysis: Significance testing and pitfalls, Nonlinear Processes Geophys., 11(11), Park, J., R. R. B. von Frese, D. A. Grejner-Brzezinska, Y. Morton, and L. R. Gaya-Pique (2011), Ionospheric detection of the 25 May 2009 North Korean underground nuclear test, Geophys. Res. Lett., 38, L22802, doi: /2011gl Rudenko, G., and A. Uralov (1995), Calculation of ionospheric effects due to acoustic radiation from an underground nuclear explosion, J. Atmos. Terr. Phys., 57(3), Šauli, P., P. Abry, J. Boška, and L. Duchayne (2006), Wavelet characterisation of ionospheric acoustic and gravity waves occurring during the solar eclipse of August 11, 1999, J. Atmos. Sol. Terr. Phys., 68(3 5), J. L. Garrison, S.-C. Lee, and Y.-M. Yang, School of Aeronautics and Astronautics, Purdue University, 701 W. Stadium Ave., West Lafayette, IN 47907, USA. (oscaryang@purdue.edu) 6of6