Review of: He, L.M., Wu, L.X., De Santis, A., Liu, S.J. and Yang, Y. (2014). Is there a one-to-one correspondence between ionsopheric anomalies and large earthquakes along Longmenshan faults? Annales Geophysicae (accepted).
This is a very interesting and timely paper. Interesting as it both shows evidence of one potential precursor to a particular earthquake (Wenchuan, China, May 2008) and, in relation to another earthquake event, shows evidence against the presence of such precursors (Ya’an, China, April 2013). This suggests the paper will be completely balanced. The paper is timely as, despite having been around for a long time, wavelets are now increasingly being used to quantify geophysical phenomena that provide a non-stationary signal (one case in point: Murphy et al. 2013, concerning periodic episodes of thermal emissions from various volcanoes).
The authors propose precursors which relate to phenomena in the ionosphere. This part of the atmosphere is influenced by many factors including solar and geomagnetic phenomena and as such, these ‘normal’ signals need to be removed from those which might be pre-seismic and to do this, a method of removing the background signal is presented (first discussed in He et al. 2012). The dataset analysed is from the global navigation satellite system and consists of the total electron content (TEC) of the ionosphere, which reflects irregularities of the ionosphere. The TEC signal was initially smoothed, so as to remove diurnal and seasonal patterns. Two wavelet methods were then applied to the dataset: the analytic wavelet transform (AWT), to detect variability in the TEC, and the cross-wavelet transform (XWT), to determine whether the changes were associated with the impending earthquake. The XWT is most pertinent here as it is applied to determine any ‘mutual relationship of two time series in the time-frequency domain’ (pg. 8); these two timeseries here are the ionospheric signal and any geophysical indices.
In relation to the Wenchuan earthquake, the solar activity was found to be low and as such, did not pollute any potentially seismic signals. What was found were signals over the region of the subsequent earthquake that were unusual, not happening in previous years or anywhere else at the same latitude; indeed they appear to be over the location of the impending earthquake (see below).
In relation the Ya’an earthquake however, the period was associated with high solar activity which had to be removed from the signal. Even applying these methods, no ionospheric anomalies could be found in the month prior to the earthquake. Interestingly, the authors note that had they not applied their own method of noise removal, they might well have concluded that these large signals were associated with the impending earthquake.
So evidently, the authors acknowledge that they do not know everything about these observations and that they cannot predict earthquakes on their basis, but what they have shown is a line of enquiry which should be explored more thoroughly. What you may be wondering however, is: how can an earthquake possibly cause changes in the ionosphere? Well the theory postulated is that radon emanations appear to increase prior to an earthquake (this is a widely proven observations see e.g. Choubey et al. 2004). This gas could ionise the lower atmosphere and as such, affect the electrical characteristics of the entire atmospheric column. Electromagnetic energy generated on rock compression (noted in Ouzounov and Freund, 2004) is also claimed as having a potential influence. So why then do some earthquakes seemingly produce such effects and other don’t? Well it might all be down to the size of the forthcoming earthquake (a greater magnitude earthquake releasing more energy), or the formation of the lithosphere which could potentially augment, or shield, some of the effects from the atmosphere.
Overall, this is an interesting study and it is great to see the presentation of both positive and negative results. I guess like most things in this field, more data is required to prove, categorically, the presence (or otherwise) of such phenomena. This work is a good step in that direction. In terms of methods applied too, this work could potentially form a reference piece for the application of wavelets. It explains their function much more comprehensively than most other studies do and, given that large proportions of scientific research focus on attempting to find correlations between datasets, the presentation of the methods that can be applied to do that is very useful. Let’s hope more research continues in the field, using techniques such as these, to confirm or refute the presence of earthquake precursors convincingly and/or, like this paper, to explain apparent anomalies.
Choubey, V.M., Mukherjee, P.K. and Ramola, R.C. (2004). Radon variation in spring water before and after Chamoli earthquake, Garhwal Himalaya, India. In: Proceeding of 11th International Congress of the International Radiation Protection Association. Madrid, Spain, 23-28 May.
He, L., Wu, L., Pulinets, S., Liu, S. and Yang, F. (2012). A nonlinear background removal method for seismo-ionospheric anomaly analysis under a complex solar activity scenario: A case study of the M9.0 Tohoku earthquake. Advances in Space Research, 50, 211–220.
Murphy, S.W., Wright, R., Oppenheimer, C. and Souza Filho, C.R., 2013, MODIS and ASTER synergy for characterizing thermal volcanic activity, Remote Sensing of Environment, 131, 195–205.
Ouzounov, D. and Freund, F. (2004). Mid-infrared emission prior to strong earthquakes analyzed by remote sensing data. Adv Space Res, 33, 268–273.