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Precise determinations of ionospheric anomaly variations associated with earthquakes require the elimination of other sources of ionospheric variabilities like ionospheric storms, geomagnetic perturbations or geophysical noise. However, revealing the seismo-ionospheric anomalies when the ionosphere is known to be a complex and nonlinear system is of utmost importance. To overcome this constraint, Hilbert-Huang transform (HHT), which is a far better technique for both nonlinear and non-stationary system like ionosphere, was applied together with the cross correlation coefficient method to a 7.0 magnitude earthquake that occurred in Mozambique on 23rd of February, 2006. Three Stations (two within the earthquake preparation zone) with hourly data of f0F2 for one month were used for the study. The results clearly revealed anomalies that are as a result of the earthquake. These were first noticed 10 days and another 3 days before the occurrence of this large earthquake.

The interests in seismo-ionospheric coupling phenomena have increased in the last decade. The variations noticed in lithosphere, atmosphere and ionosphere parameters before the main earthquakes are considered as foreknowledge of impending earthquakes (earthquake precursors). However, the tendency of using these results to provide validly early warning for upcoming earthquakes is still considered somehow controversial [

Correlation analysis is a method which has been shown to address the problem of having to distinguish between geomagnetic storms and seismo-ionospheric precursors. This is due to the fact that geomagnetic storms produce more intense disturbances in the F2-layer (critical frequency) than earthquakes [

Traditional data-analysis methods are all based on linear and stationary assumptions. Only in recent years have new methods been introduced to analyze non-stationary and non-linear data. For example, wavelet analysis and the Wagner-Ville distribution were designed for linear but non-stationary data [

The HHT consists of two parts: empirical mode decomposition (EMD) and Hilbert spectral analysis (HSA). In Empirical Mode Decomposition, the signal is decompose into a series of structural components, known as Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same number of zero-crossings and extrema. It also has symmetric envelopes defined by the local maxima and minima respectively [

According to [

Accordingly, the mean m_{1} (t) is then subtracted from the original signal

and the residual h_{1}(t) is examined as for the IMF criteria completeness. If it is an IMF then the procedure stops and the new signal under examination is the

However, if h_{1}(t) is not an IMF, the procedure, also known as “sifting”, is continued k times until the first IMF is realized.

Thus,

and finally

The sifting process continues until the last residual is either a monotonic function or a constant. The final product is a wavelet-like decomposition going from higher oscillations to lower oscillations, which means that the frequency spectrum is decreased as the order of the IMF increases. In fact, with repeated siftings, the sifting process can recover signals representing low-amplitude riding waves.

The sifting process serves two purposes: To eliminate riding waves and to make the wave profiles more symmetric. While the first purpose must be achieved for the Hilbert transform to give a meaningful instantaneous frequency, the second purpose must also be achieved in case the neighboring wave amplitudes have too large a disparity. Toward these ends, the sifting process has to be repeated as many times as is required to reduce the extracted signal to an IMF.

This study used foF2 data from the Grahamtown (Lat. 33.3S and Lon. 26.5E), Mandimo (Lat. 22.4S and Lon. 30.9E) and Louisvalle (Lat. 28.5S and Lon. 21.2E) ionospheric stations, made available by Space physic interactive data resource (SPIDR). The foF2 data are 1h sample recordings, around the time of the earthquake of magnitudes 7.0 (February, 23rd 2006). Data between 7th of February 2006 and 8th of March, 2006 (30 days or 720 hrs) were used for the study. Louisvalle station is the only station outside the earthquake preparation area, if the equation by [

Two out of the three stations are within the earthquake preparation zone so both are expected to show the ionospheric precursors. One thing that was obvious is that the ionosphere over the Lousivalle station (

difficult to say much about its pre-earthquake ionosphere. But hours after the earthquake clearly showed a different situation when compared with

On the other hand, applying the cross correlation coefficient to Grahamtown and louisvalle stations together with Grahamtown and Madimo stations confirmed the seismo-ionospheric coupling. In

This paper applied the Cross-Correlation Coefficient method, together with the Hilbert-Huang Transform, for the analysis of f0F2 around the time of an earthquake in Mozambique. Using the cross correlation coefficient method helps in eliminating from the data, disturbances in the ionosphere that might be of geomagnetic storms sources, thereby making visible variations that are considered too weak (caused by earthquake events) to be revealed. One of the things noted from Figures 1-3 is that even after four sifting processes, the signal only separated into positive and negative values as expected but however, maintained its original oscillatory mode. Being an IMF, it however has variable amplitudes as a function of time. Sifting process serves two purposes: To eliminate low-amplitude riding waves and to make the wave profiles more symmetric. While the first purpose must be achieved for the Hilbert transform to give a meaningful instantaneous frequency, the second purpose must also be achieved in case the neighboring wave amplitudes have too large a disparity [

Grahamtown station | Mandimo station | |||
---|---|---|---|---|

10 days before the earthquake | 2 hrs | From 00:00 hrs to 02:00 hrs | 9 hrs | From 00:00 hrs to 09:00 hrs |

3 days before the earthquake | 4 hrs | From 23:00 hrs (4 days to the day of earthquake) to 02:00 hrs | ||

1st day after the earthquake | 12 hrs | From 00:00 hrs to 12:00 hrs | ||

2nd day after the earthquake | 5 hrs | From 23:00 hrs ( of the 1st day after the earthquake) to 04:00 hrs | 15 hrs | From 00:00 hrs to 15:00 hrs |

S.N | Location | Date of earthquake | Time of earthquake | Intensity | Focal depth | Ionosonde stations | Location of stations | Distance from epicenter |
---|---|---|---|---|---|---|---|---|

1 | Mozambique 21.26˚S, 33.48˚E | February 23rd, 2006 | 12:19:07 local time | 7.5 (KRV) | 11 km | (1) Grahamtown | 33.3˚S, 26.5˚E | 976.1 km |

(2) Mandimo | 22.4˚S, 30.9˚E | 291.6 km | ||||||

(3) Louisvalle | 28.5˚S, 21.2˚E | 1215.8 km |

ionospheric precursors to the large earthquake and it is in accordance with the results of previous seismo- ionospheric studies.

On the other hand, the fact that Grahamtown station is 976.1 km away from the epicenter of the earthquake and the mandimo station, 291.6 km away from the epicenter was responsible for the different time responses to the impending earthquake. It is assumed that a station very close to the circumference of the circle, that is, the theoretical estimation of the earthquake preparation area, may either detect the earthquake or not. [

Special appreciation goes to Space physic interactive data resource (SPIDR) for providing the data used for this paper.

Enoch Oluwaseun Elemo, (2015) Cross Correlation Analysis of Mozambique’s 7.0 M Earthquake Using the Empirical Mode Decomposition. Open Access Library Journal,02,1-7. doi: 10.4236/oalib.1101184