DESCRIPTION:

The Illapel 2015 earthquake occurred as the result of thrust faulting on the interface between Nazca and South America plates in central Chile. The earthquake produced a 4.7-m local tsunami. The last major rupture (MS 7.9 event) occurred in the region in 1943.

 

Figure 1: Earthquake epicenter and Dobrovolsky area.

In the epicentral area, the Nazca plate is moving towards the east-northeast at a velocity of 74 mm/yr with respect to South America. The focal mechanism and the depth of the events are consistent with the occurrence on the megathrust interface in this region.

 While the former 2014 Iquique earthquake was preceded by an important precursor activity starting several months before and accelerating in the last days before the main shock, the Illapel 2015 earthquake was not preceded by significant foreshocks.

 

ANALYSES:

 

  1. SEISMOLOGY
    1. Accelerated Moment Release (AMR) & Revised-AMR

No AMR or R-AMR analyses have been performed because this EQ is too close in time with the 2014 one and the two corresponding DbAs are too overlapping (see Chile- Iquique earthquake, M8.2, 1 April 2014).

 

  1. SWARM – GEOMAGNETISM

Two different approaches were developed to search EQ precursor using geomagnetic Swarm data: MASS method and Wavelet method. Both analyses are based on Level 1B MAGxLR Swarm product.

 

  1. MASS algorithm (Magnetic Swarm anomaly detection by Spline analysis)

The algorithm MASS (Magnetic Swarm anomaly detection by Spline analysis)was applied to M8.3Chile 2015 earthquake with different thresholds, while the moving window was fixed at 3.0°. The algorithm analyses all tracks in DbA one month before and one after the EQ. The tracks are marked as “anomaly” only if the centre of the moving window is in DbA and if geomagnetic conditions are quiet. Figure 2 shows an example of anomalous tracks detected by MASS method for Chile-Illapel EQ.

 

Figure 2: Example of anomalous track in Y magnetic component (Satellite A- August 18, 2015).

The cumulative number of anomalies detected by MASS one month before and after the Chile 2015 EQ (threshold kt= 3.0) is shown in Figure 3. The cumulative number of anomaly windows shows an S-shape around 23 August, i.e. 24 days before EQ. This could be due to the activation of the fault, but we cannot exclude other external sources of these anomalies.

 

Figure 3: Cumulative number of anomaly detected by MASS one month before and one month after the Chile Illapel EQ. Threshold is kt = 3 and the anomalies are selected only with geomagnetic quiet time (|Dst| ≤ 20 nT and ap≤ 10 nT).

 

  1. Wavelet Analysis

 

The Wavelet spectral analysis has evidenced the existence of different anomalous families, each characterized by some particular features.

The following figure (Fig. 4) shows the influence of geomagnetic indices on wavelet analysis results at very low latitude: particular the higher the indices (Dst=-80 in Fig 3(left), Dst=-89 in Fig. 3(right)) the larger are the amplitude of the oscillation below -50° of geomagnetic latitude.

 

 

Figure 4: The panels (a) and (b) show wavelet results for days characterized by disturbed geomagnetic condition: in particular at very low latitude, the large and rapid oscillation is driven by highly disturbed external condition, Dst=-80 (left) and Dst=-89 (right)

 

Instead, Figure 5 shows a clear anomaly that is close to the group of epicenters but not persistent since it disappears from the successive track. On one hand, these examples evidence the extreme difficulty in the search of consolidate patterns; on the other, that it is a not easy task to explain the source of this kind of anomalies clearly emerging from data.

Even in this case, the discrimination of the source of emerging signals from the background by applying this method alone may need the adoption of some other more complex scheme.

 

Figure 5: Example of anomaly track few days before the Chile- Illapel mainshock: it is a not persistent anomaly emerging close to the group of epicenters.

 

 

  1. SWARM – IONOSPHERE from Satellite

Satellite-based data for the ionospheric characterization of the EQ-related events are mainly those referred to the LP (Langmuir Probe) instrument aboard the SWARM satellites. The electron density Ne is the relevant parameter used for the ionospheric characterization in the frame of SAFE project. Two different methods were developed to analyze Swarm ionospheric data: NeSTAD and NeLOG.

 

  1. Method I: NeSTAD

The NeSTAD analysis has been applied to the Swarm constellation data (LP and IBI data )available in the period from 17 August to 16 October 2015 have been used to derive the track anomaly parameters.The NeSTAD has been initialized with the mild outliers mode (k=1.5) and with an “excess area” parameter equal to 0.1.

Then, to tag the interesting track anomalies for this particular event, the following criteria have been applied:

  • R>Rthr=0.85 and standard deviation of the filtered track below σthr=0.1 or standard deviation of the filtered track above σthr=0.1 independently of R value.
  • Only morning tracks have been selected (02-06 LT), to remove the impact of the equatorial fountain during the day and to minimize the impact of the plasma bubble formation during night-times
  • Quiet ionospheric conditions (absolute value of Dst in the considered day not exceeding 20 nT).

An example of tagged anomaly is provided in figure 6.

 

Figure 6: Identified anomaly with the NeSTAD algorithm and tagged as interesting for the Chile M8.3 EQ event. Tagged anomaly refers to Swarm Alpha satellite on 1 September 2015.

 

 

Figure 7: - Cumulative number of anomalies identified through the NeSTAD algorithm for Swarm satellite Alpha.

 

Figure 7 shows the cumulative number of the tagged anomalies through the NeSTAD algorithm for Alpha satellite. The black dashed line indicates the day in which the Chile M8.3 EQ event occurred. The red boxes indicate the days in which disturbed geomagnetic conditions have been recorded and that are not included in the tagging process. The two blue dashed lines indicate the time interval during which the given Swarm satellite covered the DbA of the event at morning time. It is interesting to note that the period was characterized by several disturbed days from the geomagnetic point of view.

 

 

  1. Method II: NeLOG

The automatic search NeLOG of ionosphere electron density anomaly from Swarm data is applied to Chile M8.3case study. A sample is classified as anomaly if the residual value exceeds a threshold kt times the RMS of the residual after the spline fit (in this case kt=3.5). A track is selected as an “anomaly” if it has more than 10 anomaly samples in DbA and if geomagnetic indices are |Dst|<20 nT and ap<10 nT. Tracks are selected within a mean local time between 22 and 6.

 

 

Figure 8: Anomaly detected by NeLOG (satellite Alpha, 15 September 2015)before the M8.3Chile EQ.

Figure 8 shows an example of anomaly track in the date of the mainshock, while Figure 9 reports the cumulative number of anomaly windows detected by NeLOG. The R2 value indicates a deviation from linear behaviour that is an indication for possible LAIC-related effect, but such a deviation could be also due to disturbed geomagnetic conditions, and some geomagnetic disturbances could shadow any possible LAIC effect.

 

 

Figure 9:Cumulative number of anomaly samples detected by NeLOG 1 month before and 1 month after M8.3 16 September 2015 Chile EQ. Threshold is kt = 3.5, the anomalies are selected only with geomagnetic quiet time (|Dst| ≤ 20 nT and ap ≤ 10 nT) and in night time (22 ≤ LT ≤ 6).

 

  1. IONOSPHERE Ground-based

Ionosondes& GNSS

For this event, no suitable Ionosonde data were available. For GNSS analysis, the period before the event was characterised by high geomagnetic activity and not useful for the SAFE scope.

 

CONCLUSION:

The M8.3 Chile-Illapel EQ was analyzed using both Swarm geomagnetic and ionospheric data searching for earthquake-related anomalies in the frame of LAIC theory.

This event is the most intense EQ studied in this project. Unfortunately, the analyzed time window was very disturbed from the geomagnetic point of view. In particular, NeLOG algorithm detects some anomalies in the same days of magnetic anomalies found by MASS (24 days before EQ) in Alpha and Charlie satellites. However, most of these anomalies are likely caused by bubble effect over the Antarctic sea between the “Tierra del Fuego” and the Antarctic Peninsula, so cannot be related to LAIC effect.

Also in the case of NeSTAD algorithm, according to the Dst criterion most of the days before and after the event have been found to be disturbed from the geomagnetic point of view and then not suitable for the LAIC-related anomaly tagging.