VAN method

The VAN method – named after P. Varotsos, K. Alexopoulos and K. Nomicos, authors of the 1981 papers describing it[1][2] – measures low frequency electric signals, termed "seismic electric signals" (SES), by which Varotsos and several colleagues claimed to have successfully predicted earthquakes in Greece.[3][4] Both the method itself and the manner by which successful predictions were claimed have been severely criticized[5][6][7] and debated by VAN, but the critics have not retracted their views.[8][9]

Since 2001, the VAN group has introduced a concept they call "natural time", applied to the analysis of their precursors. Initially it is applied on SES to distinguish them from noise and relate them to a possible impending earthquake. In case of verification (classification as "SES activity"), natural time analysis is additionally applied to the general subsequent seismicity of the area associated with the SES activity, in order to improve the time parameter of the prediction. The method treats earthquake onset as a critical phenomenon.[10][11][12][13]

After 2006, VAN say that all alarms related to SES activity have been made public by posting at arxiv.org. One such report was posted on Feb. 1, 2008, two weeks before the strongest earthquake in Greece during the period 1983-2011. This earthquake occurred on February 14, 2008, with magnitude (Mw) 6.9. VAN's report was also described in an article in the newspaper Ethnos on Feb. 10, 2008.[14][15][16][17] However, Gerassimos Papadopolous complained that the VAN reports were confusing and ambiguous, and that "none of the claims for successful VAN predictions is justified."[18]

Description of the VAN method

Prediction of earthquakes with this method is based on the detection, recording and evaluation of seismic electric signals or SES. These electrical signals have a fundamental frequency component of 1 Hz or less and an amplitude the logarithm of which scales with the magnitude of the earthquake.[19] According to VAN proponents, SES are emitted by rocks under stresses caused by plate-tectonic forces. There are three types of reported electric signal:[4]

  • Electric signals that occur shortly before a major earthquake. Signals of this type were recorded 6.5 hours before the 1995 Kobe earthquake in Japan, for example.[20]
  • Electric signals that occur some time before a major earthquake.
  • A gradual variation in the Earth's electric field some time before an earthquake.

Several hypotheses have been proposed to explain SES:

  • Stress-related phenomena: Seismic electric signals are perhaps attributed to the piezoelectric behaviour of some minerals, especially quartz, or to effects related to the behavior of crystallographic defects under stress or strain. Series of SES, termed SES activities (which are recorded before major earthquakes), may appear a few weeks to a few months before an earthquake when the mechanical stress reaches a critical value.[2][21] The generation of electric signals by minerals under high stress leading to fracture has been confirmed with laboratory experiments.[22]
  • Thermoelectric phenomena: Alternately, Chinese researchers proposed a mechanism which relies on the thermoelectric effect in magnetite.[23]
  • Groundwater phenomena: Three mechanisms have been proposed relying on the presence of groundwater in generating SES. The electrokinetic effect is associated with the motion of groundwater during a change in pore pressure.[24] The seismic dynamo effect is associated with the motion of ions in groundwater relative to the geomagnetic field as a seismic wave creates displacement. Circular polarization would be characteristic of the seismic dynamo effect, and this has been observed both for artificial and natural seismic events.[25] A radon ionization effect, caused by radon release and then subsequent ionization of material in groundwater, may also be active. The main isotope of radon is radioactive with a half-life of 3.9 days, and the nuclear decay of radon is known to have an ionizing effect on air. Many publications have reported increased radon concentration in the vicinity of some active tectonic faults a few weeks prior to strong seismic events.[26] However, a strong correlation between radon anomalies and seismic events has not been demonstrated.[27]

While the electrokinetic effect may be consistent with signal detection tens or hundreds of kilometers away, the other mechanisms require a second mechanism to account for propagation:

  • Signal transmission along faults: In one model, seismic electric signals propagate with relatively low attenuation along tectonic faults, due to the increased electrical conductivity caused either by the intrusion of ground water into the fault zone(s) or by the ionic characteristics of the minerals.[28]
  • Rock circuit: In the defect model, the presence of charge carriers and holes can be modeled as making an extensive circuit.[29]

Seismic electric signals are detected at stations which consist of pairs of electrodes (oriented NS and EW) inserted into the ground, with amplifiers and filters. The signals are then transmitted to the VAN scientists in Athens where they are recorded and evaluated. Currently the VAN team operates 9 stations, while in the past (until 1989) they could afford up to 17.[30]

The VAN team claimed that they were able to predict earthquakes of magnitude larger than 5, with an uncertainty of 0.7 units of magnitude, within a radius of 100 km, and in time window ranging from several hours to a few weeks. Several papers confirmed this success rate, leading to statistically significant conclusion.[31] For example, there were eight M ≥ 5.5 earthquakes in Greece from January 1, 1984 through September 10, 1995, and the VAN network forecast six of these.[32]

The VAN method has also been used in Japan,[13] but in early attempts success comparable to that achieved in Greece was "difficult" to attain.[33] A preliminary investigation of seismic electric signals in France led to encouraging results.[34]

Earthquake prediction using "natural time" analysis

Since 2001 the VAN team has attempted to improve the accuracy of the estimation of the time of the forthcoming earthquake. To that end, they introduced the concept of natural time, a time series analysis technique which puts weight on a process based on the ordering of events.[10] Two terms characterize each event, the "natural time" χ, and the energy Q. χ is defined as k/N, where k is an integer (the k-th event) and N is the total number of events in the time sequence of data. A related term, pk, is the ratio Qk / Qtotal, which describes the fractional energy released. They introduce a critical term κ, the "variance in natural time", which puts extra weight on the energy term pk:

where and

Their current method deems SES valid when κ = 0.070. Once the SES are deemed valid, a second analysis is started in which the subsequent seismic (rather than electric) events are noted, and the region is divided up as a Venn diagram with at least two seismic events per overlapping rectangle. When the distribution of κ for the rectangular regions has its maximum at κ = 0.070, a critical seismic event is imminent, i.e. it will occur in a few days to one week or so, and a report is issued.[35]

Results

The VAN team claim that out of seven mainshocks with magnitude Mw>=6.0 from 2001 through 2010 in the region of latitude N 36° to N 41° and longitude E 19° to E 27°, all but one could be classified with relevant SES activity identified and reported in advance through natural time analysis. Additionally, they assert that the occurrence time of four of these mainshocks with magnitude Mw>=6.4 were identified to within "a narrow range, a few days to around one week or so."[36] These reports are inserted in papers housed in arXiv, and new reports are made and uploaded there.[37] For example, a report preceding the strongest earthquake in Greece during the period 1983-2011, which occurred on February 14, 2008, with magnitude (Mw) 6.9, was publicized in arXiv almost two weeks before, on February 1, 2008.[14] A description of the updated VAN method was collected in a book published by Springer in 2011, titled "Natural Time Analysis: The New View of Time."[38]

Natural time analysis also claims that the physical connection of SES activities with earthquakes is as follows: Taking the view that the earthquake occurrence is a phase-change (critical phenomenon), where the new phase is the mainshock occurrence, the above-mentioned variance term κ is the corresponding order parameter.[38] The κ value calculated for a window comprising a number of seismic events comparable to the average number of earthquakes occurring within a few months, fluctuates when the window is sliding through a seismic catalogue. The VAN team claims that these κ fluctuations exhibit a minimum a few months before a mainshock occurrence and in addition this minimum occurs simultaneously with the initiation of the corresponding SES activity, and that this is the first time in the literature that such a simultaneous appearance of two precursory phenomena in independent datasets of different geophysical observables (electrical measurements, seismicity) has been observed.[39] Furthermore, the VAN team claims that their natural time analysis of the seismic catalogue of Japan during the period from January 1, 1984 until the occurrence of the magnitude 9.0 Tohoku earthquake on March 11, 2011, revealed that such clear minima of the κ fluctuations appeared before all major earthquakes with magnitude 7.6 or larger. The deepest of these minima was said to occur on January 5, 2011, i.e., almost two months before the Tohoku earthquake occurrence.[40] Finally, by dividing the Japanese region into small areas, the VAN team states that some small areas show minimum of the κ fluctuations almost simultaneously with the large area covering the whole Japan and such small areas clustered within a few hundred kilometers from the actual epicenter of the impending major earthquake.[41][42]

Criticisms of VAN

Historically, the usefulness of the VAN method for prediction of earthquakes had been a matter of debate. Both positive and negative criticism on an older conception of the VAN method is summarized in the 1996 book "A Critical Review of VAN", edited by Sir James Lighthill.[43] A critical review of the statistical methodology was published by Y. Y. Kagan of UCLA in 1997.[44] Note that these criticisms predate the time series analysis methods introduced by the VAN group in 2001. The main points of the criticism were:

Predictive success

Critics say that the VAN method is hindered by a lack of statistical testing of the validity of the hypothesis because the researchers keep changing the parameters (the moving the goalposts) technique).[45]

VAN has claimed to have observed at a recording station in Athens a perfect record of a one-to-one correlation between SESs and earthquake of magnitude ≥ 2.9 which occurred 7 hours later in all of Greece.[46] However, Max Wyss said that the list of earthquake used for the correlation was false. Although VAN stated in their article that the list of earthquakes was that of the Bulletin of the National Observatory of Athens (NOA), Wyss found that 37% of the earthquakes actually listed in the bulletin, including the largest one, were not in the list used by VAN for issuing their claim. In addition, 40% of the earthquake which VAN claimed had occurred were not in the NOA bulletin.[47] Examining the probability of chance correlation of another set of 22 claims of successful predictions by VAN of M > 4.0 from January 1, 1987 through November 30, 1989 [48] it was found that 74% were false, 9% correlated by chance, and for 14% the correlation was uncertain. No single event correlated at a probability greater than 85%, whereas the level required in statistics for accepting a hypothesis test as positive would more commonly be 95%.[49]

In response to Wyss' analysis of the NOA findings, VAN said that the criticisms were based on misunderstandings.[50] VAN said that the calculations suggested by Wyss would lead to a paradox, i.e., to probability values larger than unity, when applied to an ideal earthquake prediction method.[51] Other independent evaluations said that VAN obtained statistically significant results.[31][32]

Mainstream seismologists remain unconvinced by any of VAN's rebuttals. In 2011 the ICEF concluded that the optimistic prediction capability claimed by VAN could not be validated.[52] Most seismologists consider VAN to have been "resoundingly debunked".[53]

Proposed SES propagation mechanism

An analysis of the propagation properties of SES in the Earth’s crust showed that it is impossible that signals with the amplitude reported by VAN could have been generated by small earthquakes and transmitted over the several hundred kilometers between the epicenter and the receiving station.[54] In effect, if the mechanism is based on piezoelectricity or electrical charging of crystal deformations with the signal traveling along faults, then none of the earthquakes which VAN claimed were preceded by SES generated an SES themselves. VAN answered that such an analysis of the SES propagation properties is based on a simplified model of horizontally layered Earth and that this differs greatly from the real situation since Earth's crust contains inhomogeneities. When the latter are taken into account, for example by considering that the faults are electrically appreciably more conductive than the surrounding medium, VAN believes that electric signals transmitted at distances of the order of one hundred kilometers between the epicenter and the receiving station have amplitudes comparable to those reported by VAN.[28] Susan Hough noted that this amounted to special pleading, making VAN's hypothesis un-falsifiable because it relies on unrepeatable circumstances.[53]

Electromagnetic compatibility issues

VAN’s publications are further weakened by failure to address the problem of eliminating the many and strong sources of change in the magneto-electric field measured by them, such as telluric currents from weather, and electromagnetic interference (EMI) from man-made signals. One critical paper (Pham et al. 1998) clearly correlates an SES used by the VAN group with digital radio transmissions made from a military base.[55] In a subsequent paper, VAN said that such noise coming from digital radio transmitters of the military database has been clearly distinguished from true SES by following the criteria developed by VAN.[56] Further work in Greece by Pham et al. in 2002 has tracked SES-like "anomalous transient electric signals" back to specific human sources, and found that such signals are not excluded by the criteria used by VAN to identify SES.[57]

Public policy

Finally, one requirement for any earthquake prediction method is that, in order for any prediction to be useful, it must predict a forthcoming earthquake within a reasonable time-frame, epicenter and magnitude. If the prediction is too vague, no feasible decision (such as to evacuate the population of a certain area for a given period of time) can be made. In practice, the VAN group issued a series of telegrams in the 1980s, warning of impending earthquakes that did not occur, or did not occur within the parameters listed in the telegrams. During the same time frame, the technique also missed major earthquakes.[58] These inaccurate predictions from the early VAN method led to public criticism and the cost associated with false alarms generated ill will.[59] Major opponents of VAN were the Greek seismologists Vassilis Papazachos and G. Stavrakakis. The debate between Papazachos and the VAN team has repeatedly caused public attention in their home country Greece and has been extensively discussed in the Greek media.

See also

Notes

  1. ↑ Varotsos, Alexopoulos & Nomicos 1981a, 1981b
  2. 1 2 Varotsos & Alexopoulos 1984
  3. ↑ Varotsos & Kuhlanek 1993 (preface to a special edition about VAN)
  4. 1 2 Varotsos, Alexopoulos & Lazaridou 1993
  5. ↑ Mulargia & Gasperini 1992
  6. ↑ Geller 1997, §4.5
  7. ↑ ICEF 2011, p. 335
  8. ↑ Lighthill 1996 (proceedings of a conference that reviewed VAN)
  9. ↑ twenty articles in a special issue of Geophysical Research Letters (table of contents)
  10. 1 2 Varotsos, Sarlis & Skordas 2002; Varotsos 2006.
  11. ↑ Rundle et al. 2012.
  12. ↑ Huang 2015.
  13. 1 2 Uyeda, Kamogawa & Tanaka 2009
  14. 1 2 Uyeda & Kamogawa 2008
  15. ↑ Uyeda 2010
  16. ↑ Apostolidis 2008.
  17. ↑ Chouliaras 2009
  18. ↑ Papadopoulos 2010
  19. ↑ Varotsos, Alexopoulos & Nomicos 1981a; Varotsos et al. 1981; Varotsos, Alexopoulos & Nomicos 1982.
  20. ↑ Matsumoto, Ikeya & Yamanaka 1998.
  21. ↑ Varotsos et al. 1986, p. 120.
  22. ↑ Hadjicontis et al. 2007
  23. ↑ Shen et al. 2011.
  24. ↑ Gershenzon, Gokhberg & Yunga 1993.
  25. ↑ Honkura et al. 2009.
  26. ↑ Pulinets 2007.
  27. ↑ ICEF 2011, p. 334.
  28. 1 2 Varotsos et al. 1998.
  29. ↑ Freund 1998.
  30. ↑ Varotsos & Lazaridou 1991
  31. 1 2 Hamada 1993
  32. 1 2 Uyeda 1996
  33. ↑ Utada 1993, p. 153
  34. ↑ Maron et al. 1993
  35. ↑ Varotsos, Sarlis & Skordas 2011, Chapter 7.
  36. ↑ Varotsos, Sarlis & Skordas 2011, p. 326
  37. ↑ Lazaridou-Varotsos 2013, pp. 169–170
  38. 1 2 Varotsos, Sarlis & Skordas 2011
  39. ↑ Varotsos et al. 2013
  40. ↑ Sarlis et al. 2013
  41. ↑ Sarlis et al. 2015
  42. ↑ Huang 2015
  43. ↑ Lighthill 1996.
  44. ↑ Kagan 1997, p. 512.
  45. ↑ Mulargia & Gasperini 1992; Mulargia & Gasperini 1996; Wyss 1996b.
  46. ↑ Varotsos, Alexopoulos & Nomicos 1981b.
  47. ↑ Wyss 1996a.
  48. ↑ Varotsos & Lazaridou 1991.
  49. ↑ Wyss & Allmann 1996.
  50. ↑ Varotsos et al. 1996a
  51. ↑ Varotsos et al. 1996b
  52. ↑ ICEF 2011, pp. 335–336.
  53. 1 2 Hough 2010, p. 195
  54. ↑ Bernard 1992; Bernard & LeMouel 1996.
  55. ↑ Pham et al. 1998.
  56. ↑ Sarlis et al. 1999
  57. ↑ Pham et al. 2002.
  58. ↑ Hamada 1993.
  59. ↑ Mulargia & Geller 2003, p. 318.

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