VAN method

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The VAN method – named after P. Varotsos, K. Alexopoulos and K. Nomicos, authors of the 1981 papers describing it[1] – measures suspected "seismic electric signals" (SES), by which Varotsos and several colleagues claim to have successfully predicted earthquakes in Greece.[2] Both the method itself and the manner by which successful predictions are claimed have been severely criticized;[3] the International Commission on Earthquake Forecasting for Civil Protection declared: "subsequent testing has failed to validate the optimistic SES prediction capability claimed by the authors".[4] The VAN method was revised in 2001, and this new method has been independently reproduced.[5] It awaits further independent verification.

Description of the VAN method[edit]

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 proportional to the magnitude of the earthquake.[6] According to VAN proponents, SES are emitted by rocks under stresses caused by plate-tectonic forces. There are three types of reported electric signal:[7]

  • Electric signals that occur at the same time as a major earthquake. Signals of this type were recorded 6.5 hours before the 1995 Kobe earthquake in Japan, for example.[8]
  • 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. These may appear a few weeks before an earthquake, when the mechanical stress reaches a critical value.[9] The generation of electric signals by minerals under high stress leading to fracture has been confirmed with laboratory experiments.[10]
  • Thermoelectric phenomena: Alternately, Chinese researchers proposed a mechanism which relies on the thermoelectric effect in magnetite.[11]
  • 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.[12] 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.[13] 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.[14] However, a strong correlation between radon anomalies and seismic events has not been demonstrated.[15]

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.[16]
  • Rock circuit: In the defect model, the presence of charge carriers and holes can be modeled as making an extensive circuit.[17]

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 (1999) they could afford up to 17.[18]

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 a 2-hour to 11-day time window. Several papers confirmed this success rate, but the earthquake sample size was too small to make a statistically significant conclusion.[19] For example, there were eight M ≥ 5.5 earthquakes in Greece from January 1, 1984 through September 10, 1995, and the VAN network claims to have forecast six of these.[20]

The VAN method has also been used in Japan,[21] but in early attempts success was "difficult" to attain.[22] A preliminary study of sites for investigation of seismic electric signals in France was abandoned based on criticism of the first VAN method.[23]

Earthquake prediction using "natural time" analysis[edit]

Since 2001 the VAN team has tried to improve the accuracy of the estimation of the time of the forthcoming earthquake. Their new method involves the introduction of the concept of natural time, a time series analysis technique which puts weight on a process based on the ordering of events.[24] They define a variance term κ in the time series analysis. Their current method detects SES as valid when κ = 0.070. That is the first part of their protocol. Once the SES are deemed valid, a second analysis is started. All the seismic (not electric) events are now 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, the critical seismic event is imminent, and a prediction is issued.[25]

Here is a brief introduction to the analysis. Two terms, χ and Q, characterize each event. 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. Q is the energy released for each event. A related term, p, is the ratio Q/Q(total), and describes the fractional energy released. They introduce a critical term κ, defined as κ = [ Σ p(k) (k/N)^2 ] − [ Σ (k/N) p(k) ]^2, where κ is the variance in natural time, k is the event index, N is the number of events, Σ signifies summation, for k = 1 to N, and p(k) is the fractional quantity of energy for the k-th event. This variance puts extra weight on the energy term, p(k).

The VAN team claims to have successfully predicted twenty five of the 28 major earthquakes from 2001 through 2010 in the region of latitude N 36° to N 41° and longitude E 19° to E 27° with this new method.[26] Predictions are part of papers housed in arXiv, and new predictions are currently being made and uploaded there.[27] 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."[28]

Criticisms of VAN[edit]

Currently, the major criticism of the VAN method is that results have not yet been replicated by scientists outside specific research groups in Greece and Japan. Testing of the method needs to be done by scientists unrelated to these two groups. Independent verification is a standard protocol in science.

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.[29] A critical review of the statistical methodology was published by Y. Y. Kagan of UCLA in 1997.[30] 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: 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.[31] However, it was later shown 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), it was 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.[32] Examining the probability of chance correlation of 22 claims of successful predictions by VAN of M > 4.0 from January 1, 1987 through November 30, 1989 [33] it was found that 74% were false, 9% correlated by chance, and for 14% the correlation was uncertain.[34] 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%.
  • 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.[35] 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. There is also some doubt that the phenomena of rock physics seen in certain laboratory conditions can be assumed to take place in the Earth’s seismogenic crust.
  • 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.[citation needed] One critical paper clearly correlates an SES used by the VAN group with digital radio transmissions made from a military base.[36]
  • Scientific reporting: Most importantly, the method is hindered by a lack of statistical testing of the validity of the VAN hypothesis because the researchers keep changing the parameters of the hypothesis (the moving goalpost technique).[37]
  • 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.[38] These inaccurate predictions from the early VAN method led to public criticism and the cost associated with false alarms generated ill will.[39] 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.[citation needed]

See also[edit]


  1. ^ Varotsos, Alexopoulos & Nomicos 1981a, 1981b. Varotsos & Alexopoulos 1984 and Mulargia & Gasperini 1992 (pp. 32, 36) cite a paper – "Electric signals predicting earthquakes" – by the same authors said to be have been presented at the 1981 4th International Conference on Basement Tectonics, but the record shows no such paper. See also Kagan 1997, §3.3.1, p. 512.
  2. ^ Varotsos & Kuhlanek 1993 (preface to a special edition about VAN); Varotsos, Alexopoulos & Lazaridou 1993. See also Geller 1997, §8.2.
  3. ^ Mulargia & Gasperini 1992; Lighthill 1996 (proceedings of a conference that reviewed VAN); Geller 1997, §4.5; and twenty articles in a special issue of Geophysical Research Letters (table of contents).
  4. ^ ICEF 2011, p. 335.
  5. ^ Uyeda, Kamogawa & Tanaka 2009.
  6. ^ Varotsos, Alexopoulos & Nomicos 1981a; Varotsos et al. 1981; Varotsos, Alexopoulos & Nomicos 1982.
  7. ^ Varotsos, Alexopoulos & Lazaridou 1993.
  8. ^ Matsumoto, Ikeya & Yamanaka 1998.
  9. ^ Varotsos et al. 1986, p. 120.
  10. ^ Hadjicontis et al. 2007; Hadjicontis, Eftaxias & Varotsos 1988.
  11. ^ Shen et al. 2011.
  12. ^ Gershenzon, Gokhberg & Yunga 1993.
  13. ^ Honkura et al. 2009.
  14. ^ Pulinets 2007.
  15. ^ ICEF 2011, p. 334.
  16. ^ Varotsos et al. 1998.
  17. ^ Freund 1998.
  18. ^ Varotsos & Lazaridou 1991.
  19. ^ Hamada 1993.
  20. ^ Uyeda 1996.
  21. ^ Uyeda, Kamogawa & Tanaka 2009.
  22. ^ Utada 1993, p. 153.
  23. ^ Maron et al. 1993.
  24. ^ Varotsos, Sarlis & Skordas 2002; Varotsos 2006.
  25. ^ Varotsos, Sarlis & Skordas 2011, Chapter 7.
  26. ^ Varotsos, Sarlis & Skordas 2011, p. 326.
  27. ^
  28. ^ Varotsos, Sarlis & Skordas 2011.
  29. ^ Lighthill 1996.
  30. ^ Kagan 1997, p. 512.
  31. ^ Varotsos, Alexopoulos & Nomicos 1981b.
  32. ^ Wyss 1996a.
  33. ^ Varotsos & Lazaridou 1991.
  34. ^ Wyss & Allmann 1996.
  35. ^ Bernard 1992; Bernard & LeMouel 1996.
  36. ^ Pham et al. 1998.
  37. ^ Mulargia & Gasperini 1992; Mulargia & Gasperini 1996; Wyss 1996b.
  38. ^ Hamada 1993.
  39. ^ Mulargia & Geller 2003, p. 318.


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