the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 20 Feb 2024
Investigation of geomagnetic field variations in search of seismo-electromagnetic emissions associated with earthquakes in subduction zone of Andaman-Nicobar, India
Abstract. The study of seismo-electromagnetic (EM) emissions has the potential to provide new insights into the physics of seismic activity and improve our ability to monitor and predict earthquakes and other geophysical events. Continuous recording and monitoring of EM fields in seismically active areas are very complex, but it can open a new regime in the field of earthquake prediction. In this study, one year of ground based geomagnetic data during March 2019 to April 2020 in seismic active subduction zone of Andaman-Nicobar region in search of EM signatures related to lithospheric processes. An anomalous signature in the vertical component of geomagnetic field is preferred to study after removing the global and seasonal effect from the data. Apart from vertical component of geomagnetic field, polarization ratios which also include horizontal component, also studied from spectral density with the same purpose in ULF range. Over the duration of one year, we noted an 80 % enhancement in polarisation ratios and 67 % deviations in diurnal ratios average 18 days before of earthquake events. Apart from that, the significant enhancements in diurnal and polarization ratio were shown to be successfully correlated with 11 out of 14 earthquakes which is equivalent to approximately 78 % success ratio.
Status: closed
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RC1: 'Comment on egusphere-2024-177', Anonymous Referee #1, 12 Mar 2024
This paper explores the potential of seismo-electromagnetic emissions in understanding seismic activity and enhancing earthquake monitoring and prediction. The authors analyzed geomagnetic data from the Andaman subduction zone spanning March 2019 to April 2020. They focused on detecting anomalous signatures in the vertical component of the geomagnetic field after eliminating global and seasonal effects. Additionally, they examined polarization ratios derived from spectral density in the ULF range. Over the year-long period, they observed an 80% increase in polarization ratios and 67% deviations in diurnal ratios, occurring approximately 18 days before earthquake events. These enhancements were found to be correlated with 11 out of 14 earthquakes, indicating a success rate of approximately 78% for the study.
Unfortunately the work presents several problems and cannot be published in the present form.
Major problems.
- No discrimination between quiet and disturbed magnetic days. It is known that geomagnetic external perturbations (storms, substorms, bays) produce similar effects on the signal than potential earthquake related anomalies. It is suggested to exclude periods of geomagnetic activity characterized by high values of geomagnetic indices (e.g. Kp, Dst, AE)
- No confutation analysis. The method must be validated considering a comparable period without seismicity to see how the method behave. If the number of anomalies are comparable, the method does not work.
- Range in earthquake magnitudes just limited between 4.5 and 5.3. One would expect that magnitude and distance of earthquake with respect to the geomagnetic station affect the geomagnetic field differently, increasing the amplitude of anomaly with magnitude or with inverse of distance. To have a reliable statistics a large range of magnitudes is necessary. In addition, the work considered 63 earthquakes, then selected 15 “groups” of earthquakes (Figure 8), that were then reduced to 14 (Table 2).
- Lines 178-191. The chosen thresholds (from one sigma to 0.125 sigma, at 0.5 interval of standard deviation) are not robust to detect anomalies. An anomaly should be some signal that clearly emerges from the background. For the chosen thresholds, this is not the case: in this case the anomalies could be simply due to chance.
Minor points
- The sentence from line 12 to line 13 has no verb. I suggest to insert “has been analysed” in line 13, just after “region”.
- Line 15. Please correct “seasonal effects”.
- Line 42. Please delete “been” in “have been studied”.
- Line 54. Please correct “earthquakes”.
- The sentence that starts from line 75 is not clear. There is a list of earthquakes, probably earthquakes occurred before 2000. Therefore, specify it.
- In line 78 the magnitude attributed to the Dec. 26 2004 earthquake is 9.0, while in the next line 83, is attributed as 9.1 Mw.
- Figure 1. The acronym AS (Andaman Trench of the Sumatran Fault System) mentioned in the caption, is not found in the figure. By the way, the caption is poorly written: for instance, it is not clear which geomagnetic station is represented by a triangle (Campbell Bay, Great Nicobar, mentioned in the Data?).
- Line 105. What is “MSL”? mean sea level? Please specify.
- Lines 120-121. The distance is probably taken from earthquakes and geomagnetic station. Please specify.
- List of earthquakes in Table 1. It is evident that no declustering was applied: there are many earthquakes very close in time.
- Line 140. Please correct “indicates”
- Figure 3. Please insert “the anomaly” before “detection”.
- Line 156. The sentence “A ratio >1 indicates the suppression in amplitude of Z-component..” is not clear to me. The ratio is Z/H. Do you mean “…in amplitude of H-component”?
- Line 182. Please delete “is” before “significantly”.
- Line 256. What is “CBY”? Is it the station Campbell Bay? Please specify (of course the first time you introduce the geomagnetic station).
- Line 330. It is introduced the concept of skin depth without any definition or reference.
- Line 334. Please correct “H field”
- Line 344. Please correct “2 months before at stations ESA and MR”
- Line 373. Please write “up to”
- Lines 400-402. Please add some references.
- Line 416, Please write “may facilitate to understand” (delete “to facilitate”)
Citation: https://doi.org/10.5194/egusphere-2024-177-RC1 -
AC1: 'Reply on RC1', Rahul Prajapati, 17 Apr 2024
Dear Editor-in-Chief,
We take this opportunity to thank you, and Referee 1 for thoughtful comments on our manuscript which helped us in improving the manuscript. We hope that the answer of each major and minor comment will meet your expectations. The comments of the reviewers and their replies are listed here one by one, which includes two figures. We request to please go through the attached file in the supplement for figures.
Yours sincerely,
Rahul Prajapati, Kusumita Arora
Reviewer comments # 1
Major comments.
Comment 1. No discrimination between quiet and disturbed magnetic days. It is known that geomagnetic external perturbations (storms, substorms, bays) produce similar effects on the signal than potential earthquake related anomalies. It is suggested to exclude periods of geomagnetic activity characterized by high values of geomagnetic indices (e.g. Kp, Dst, AE)
Answer 1. In the proposed study, we have already selected the anomalies from quiet time by selecting days where kp<3and removed the anomalies correspond to kp>3 (line number 137). Additionally, following the suggestion from the comment, we again compared these anomalous signatures with the DST index for the same duration of study and found that it lies between -50 and +40, which indicates the absence of any storms or substorms (Figure 1). Thus, in the proposed work, the anomalies computed from the vertical component of geomagnetic data are possibly free from the effect of any external origin. We prefer to use only the kp and Dst indices because these indices are computed from lower and middle latitude observatories, and our study also lies in this region only, while the AE index is computed from observatories in the polar region to quantify the geomagnetic activity in the polar region. Thus, we have avoided using the AE index in our study.
Figure 1. The anomalies from vertical component of geomagnetic data (a) diurnal ratio, polarization ratio (b) Z/H, and (c) Z/G, along with geomagnetic indices (d) Kp, and (e) Dst.
Comment 2. No confutation analysis. The method must be validated considering a comparable period without seismicity to see how the method behave. If the number of anomalies are comparable, the method does not work.
Answer 2. Thank you for the point. In this regard, we have tested the same method on the data of the mid-latitude geomagnetic observatory in Hyderabad, India, from March 2019 to March 2020, which has nearly the same duration as the Campbell Bay data. The geomagnetic observatory of Hyderabad is located in Deccan-Shield, which is a completely aseismic zone. The final result we obtained from the Hyderabad data was compared with the final result of the Campbell data, and we noted that in the diurnal ratio, the only anomaly of 28–29 November 2019 partly matches the anomaly of the Hyderabad data from October 22 to November 2, 2019, which is completely absent in the polarisation ratio of Hyderabad. Apart from that, the anomalies in the polarisation ratio of Campbell Bay and Hyderabad are not comparable to any extent. Thus, we believe that the data recorded in the tectonic active region is more likely to record the EM signatures from pre-earthquake processes, and the significant enhancements that appear within an acceptable range of days prior to earthquakes show that the method works well. The comparative figure of the final result of Hyderabad and Campbell data is shown in the below figure.
Figure 2. Diurnal ratio anomalies from vertical component of geomagnetic data (a) Campbell data, (b) Hyderabad data. Polarization ratio anomalies (c), Campbell data (d), Hyderabad data.
Comment 3. Range in earthquake magnitudes just limited between 4.5 and 5.3. One would expect that magnitude and distance of earthquake with respect to the geomagnetic station affect the geomagnetic field differently, increasing the amplitude of anomaly with magnitude or with inverse of distance. To have a reliable statistic a large range of magnitudes is necessary. In addition, the work considered 63 earthquakes, then selected 15 “groups” of earthquakes (Figure 8), that were then reduced to 14 (Table 2).
Answer 3. In the proposed study, from May 2019 to Apr 2020 (duration of study) faces the earthquakes with magnitude range from 4.5 to 5.3 the duration of study. Thus, due to insufficient length of data it was difficult to achieve such objective in present study. The similar type of work is also carried out by Bulusu et al. (2023) and Ida et al. (2012) which supports our study. Bulusu et al. (2023) has identified the anomalous EM signatures (from vertical component of geomagnetic signal) associated with moderate magnitude earthquakes (3.5 ) occurred near to Main Central Thrust (MCT) in Kumaun Himalaya region, India. Similarly, Ida et al. (2012) analysed ULF geomagnetic data at Kashi station, China approximately for four years where several moderate earthquakes occurred within 100-125 km radius of recording station and reported significant changes in vertical component of geomagnetic field prior to the earthquakes.
Figure 8 represents the amplitudes of anomalies of diurnal ratio and polarization ratio correlatable with earthquakes occurring during or after these anomalies. The first dense cluster of 45 earthquakes occurring from end of March 2019 to mid-April 2019 are not included in this figure, as the data length before the occurrence of this cluster is insufficient. The horizontal axis represents earthqaurs or group of earthquakes, which are possibly associated with preceded anomalous signatures instead of whole declustered earthquake from earthquake CatLog.
Comment 4. Lines 178-191. The chosen thresholds (from one sigma to 0.125 sigma, at 0.5 interval of standard deviation) are not robust to detect anomalies. An anomaly should be some signal that clearly emerges from the background. For the chosen thresholds, this is not the case: in this case the anomalies could be simply due to chance.
Answer 4. Han et al. (2015) used threshold value and found a single anomalous signature in vertical component of geomagnetic field prior to two month of Tohoku earthquake M9.0. Similarly, Yousof et al. (2019) used threshold value to identify the anomalous signature in vertical component of geomagnetic field and found a single anomaly two weeks before the Visayas, Philippines earthquake M6.9, 2012. Habora et al. (2004) used threshold condition and identified the anomalous signature in geomagnetic data prior to earthquake occurred on Izu island of magnitude between 6 and 6.5. Habora et al. (2004) also tested threshold condition and noted the isolated anomalies correspond to same earthquakes. Moreover, Arora et al. (2012) analysed the geomagnetic signal of Koyna region to study the anomalous EM signatures from earthquakes occurred due to induced reservoir seismicity with magnitude 2.5 to 4.0 and noted few anomalous signatures in polarization ratio. In this study, Arora et al. (2012) used mean value of polarization ratio by adding 0.27 and 0.72 as a threshold condition to identify the significant variation in polarization ratios.
As the magnitudes of the earthquakes in study duration are moderate (4.5<M<5.3) and occurrence frequency is monthly on an average, it was necessary to lower the thresholds in order to detect the anomalies at all. Also, we have used nighttime data for polarization ratio as well as restricted the values of Kp and Dst indices. Hence we feel that the current thresholds are justified. In Figure 2 above, we see that application of the same thresholds on data from an aseismic site does not produce any anomalies, which further validates our approach.
Minor points:
- The sentence from line 12 to line 13 has no verb. I suggest to insert “has been analysed” in line 13, just after “region”.
Answer: Revised (line number 13)
- Line 15. Please correct “seasonal effects”.
Answer: Corrected ((line number 13)
- Line 42. Please delete “been” in “have been studied”.
Answer: corrected ((line number 42)
- Line 54. Please correct “earthquakes”.
Answer: Corrected ((line number 54)
- The sentence that starts from line 75 is not clear. There is a list of earthquakes, probably earthquakes occurred before 2000. Therefore, specify it.
Answer: Sentence revised ((line number 74-78)
- In line 78 the magnitude attributed to the Dec. 26 2004 earthquake is 9.0, while in the next line 83, is attributed as 9.1 Mw.
Answer: Corrected ((line number 83)
- Figure 1. The acronym AS (Andaman Trench of the Sumatran Fault System) mentioned in the caption, is not found in the figure. By the way, the caption is poorly written: for instance, it is not clear which geomagnetic station is represented by a triangle (Campbell Bay, Great Nicobar, mentioned in the Data?).
Answer: Figure 1 is replaced by revised figure including the correction of AS by AT. The figure caption is also revised (Page No. 5).
- Line 105. What is “MSL”? mean sea level? Please specify.
Answer: The sentence is revised by specifying the MSL as mean sea level ((line number 106).
- Lines 120-121. The distance is probably taken from earthquakes and geomagnetic station. Please specify.
Answer: Sentence is revised (line 123)
- List of earthquakes in Table 1. It is evident that no declustering was applied: there are many earthquakes very close in time.
Answer: Table 1 showing the all earthquakes available in ISC CatLog, while Table 2 showing the declustured earthquakes with details of preceding anomalies or possible EM signature from pre-earthquake processes.
- Line 140. Please correct “indicates”
Answer: Corrected ((line number 142)
- Figure 3. Please insert “the anomaly” before “detection” ((line number 149-150).
Answer: Revised
- Line 156. The sentence “A ratio >1 indicates the suppression in amplitude of Z-component.” is not clear to me. The ratio is Z/H. Do you mean “…in amplitude of H-component”?
Answer: in this section we discussed about diurnal ratio i.e. ratio of regular diurnal and daily diurnal. The regular diurnal constructed from best quiet days of each month, by taking the ratio the background signal in daily diurnal is minimised and close to 1. But if there is small amplitude of diurnal field (due to superimpose of other field) the ratio will be greater than 1. Thus from time series of ratio of regular and daily diurnal ratio, it is easy to identify the anomalous Z-field by tracing the ratio greater than 1.
- Line 182. Please delete “is” before “significantly”.
Answer: Corrected
- Line 256. What is “CBY”? Is it the station Campbell Bay? Please specify (of course the first time you introduce the geomagnetic station).
Answer: Sentence is revised (line 258).
- Line 330. It is introduced the concept of skin depth without any definition or reference.
Answer: Sentence is revised (line 332-333).
- Line 334. Please correct “H field”
Answer: Corrected ((line number 337)
- Line 344. Please correct “2 months before at stations ESA and MR”
Answer: Sentence revised ((line number 347-348)
- Line 373. Please write “up to”
Answer: sentence revised (line 377)
- Lines 400-402. Please add some references.
Answer: Sentence is revised and reference added ((line number 404-406).
- Line 416, Please write “may facilitate to understand” (delete “to facilitate”)
Answer: Sentence is corrected (line number 420).
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RC2: 'Comment on egusphere-2024-177', Anonymous Referee #2, 12 Apr 2024
In this investigation, the author attempts to correlate ULF geomagnetic anomalies to 63 seismic activities occurred within 250 km from the observatory site during 2019 to 2020. To identify geomagnetic anomalies associated with lithospheric processes, three approaches have been utilized: diurnal ratio, polarization ratio I SZ/SH and II SZ/SG. The results have presented that geomagnetic anomalies appear before the large percent of earthquakes.
However, there are still some major or minor unclear issues:
- There are some grammar or express mistakes but it is not easy to point them out because there is no line number in the manuscript.
- In Figure 1, there are some earthquakes and related numbers added together and it is no easy to figure out and the resolution is also not enough, including Figure 3.
- It is maybe better for Table 1 acting as an appendix?
- We find no more useful information in Figure 2, or it can be compared with that of raw data.
Citation: https://doi.org/10.5194/egusphere-2024-177-RC2 -
AC2: 'Reply on RC2', Rahul Prajapati, 22 Apr 2024
Dear Editor-in-Chief,
We take this opportunity to thank you, and referee 1 for thoughtful comments on our manuscript which helped us in improving the manuscript. We hope that the answer of each major and minor comments will meet your expectations. the figure discussed in text of reply is included in pdf file attached in spplement section, so please refer to attached file also. In attached pdf, the comments of the reviewers are shown in red color, our reply in normal font and black color.
Yours sincerely,
Rahul Prajapati, Kusumita Arora
Reviewer comments # 2
Minor and Major comments.
Comment 1. There are some grammar or expression mistakes but it is not easy to point them out because there is no line number in the manuscript.
Answer 1. We have thoroughly checked and revised sentences and corrected grammar mistakes in the manuscript according to suggestions of reviewer.
Comment 2. In Figure 1, there are some earthquakes and related numbers added together and it is no easy to figure out and the resolution is also not enough, including Figure 3.
Answer 2. A swarm of earthquakes (numbered from 1 to 45) occurs at the beginning of the study period. These earthquakes are concentrated in a very small area and representative circles overlap each other. Thus it is difficult to resolve the earthquakes and their numbers separately. The resolution of the original figure was good and its size was 23672 kb. We are again uploading the high resolution figures of 1 and 3 in supplementary section for your kind review. An enlarged view of the earthquake cluster area is additionally shown here Figure S.
Figure S. Enlarge view of earthquake event clustered region shown in rectangle of figure 1.
Figure 1. Bathymetry map of Andaman-Nicobar subduction zone (modified after Cochran et al., 2010; E. Anusha et al., 2020). The faults are AT (the Andaman Trench of the); SS (the Seulimeum strand); WAF (the West Andaman Fault) of Sumatran Fault System. The green, pink, and red circles are the earthquakes are associated with AT, WAF, and SS faults respectively. the location of Campbell Bay geomagnetic station shown by triangle.
Figure 3. Schematics of work flow of diurnal ratio and polarization approach in the anomaly detection of EM signature in ULF range.
Comment 3. It is maybe better for Table 1 acting as an appendix?
Answer 3. We have analysed our results in the Result and Discussion sections with reference to earthquakes by its number only, which is mentioned in Table 1. Thus we believe that Table 1 should be included in the manuscript.
Comment 4. We find no more useful information in Figure 2, or it can be compared with that of raw data.
Answer 4. The purpose of including the figure 2 is to demonstrate the quality of data and data gaps. Figure 2 shows clearly the quality of data and its availability is enough good for further processing to meet our objectives. The raw data will again show same information and its comparison with present data (shown in figure 2) will not give any additional information. Thus, we believe that inclusion of figure 2 in the present form is appropriate.
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RC3: 'Comment on egusphere-2024-177', Anonymous Referee #3, 02 May 2024
The paper is about identification of seismo-electromagnetic anomaly as an earthquake precursor from the geomagnetic field time series recorded using digital fluxgate magnetometers at an observatory. Earthquakes occurring around 250 Km radius of this observatory are considered for their precursory signature. Analysis of data is presented through two methods namely diurnal ratio and polarization ratio. In the diurnal ratio method authors have considered hourly mean, thereby filtering high frequency variations and considered mean from quiet day variation for defining diurnal ratio. Similarly, for polarization analysis local night time data is utilized and polarization ratio (SZ/SH and SZ/SG) is calculated. For the calculation authors have used frequency band from 0.001 to 0.01 Hz. Amplitude variation beyond μ + 0.25σ for diurnal ratio and beyond μ + 0.5σ for polarization ratio is considered as anomalous variation.
The major problem is considered amplitude anomalies are correlated with individual or group of earthquakes of different magnitude, earthquakes from different epicentral distances, earthquakes from different depth. How an amplitude anomaly is giving directional indications? Further it is not clear how the variation of earthquake parameters are affecting identified anomaly. I suggest rather than associating anomalies to particular earthquake, it would be better to say that there exist seismo-magnetic anomalies in the data but relating it with particular earthquake require some kind of directional analysis of these signatures, which further require datasets from more than one observatory.
Whether polarization ratio is calculated for discrete frequencies or for entire frequency range 0.001 to 0.01 Hz. If it is for discrete frequencies, then frequencies need to be mentioned and their variations must be shown for individual frequency. If it is calculated for entire ulf frequency range, then a rational must be given why it is done? I suggest to analysis polarization ratio at different discrete frequencies or small period bands. This would be helpful relating any seismomagnetic signature to depth.
In light of above I suggest a revision of the paper. However, I appreciate authors effort in this field of study, which is still in infancy and require enormous amount of data.
Citation: https://doi.org/10.5194/egusphere-2024-177-RC3 -
AC3: 'Reply on RC3', Rahul Prajapati, 09 May 2024
Dear Editor-in-Chief,
We take this opportunity to thank you, and referee 3 for thoughtful comments on our manuscript which helped us in improving the manuscript. We hope that the answers to each major and minor comment will meet your expectations. The figure discussed in the text of the reply is included in pdf file attached in supplement section, so please refer to the attached file also. In the attached pdf, the comments of the reviewers are shown in red color, and our reply in normal font and black color.
Yours sincerely,
Rahul Prajapati, Kusumita Arora
Reviewer comments # 3
Comment 1: The major problem is considered amplitude anomalies are correlated with individual or group of earthquakes of different magnitude, earthquakes from different epicentral distances, earthquakes from different depth. How an amplitude anomaly is giving directional indications? Further it is not clear how the variation of earthquake parameters are affecting identified anomaly. I suggest rather than associating anomalies to particular earthquake, it would be better to say that there exist seismo-magnetic anomalies in the data but relating it with particular earthquake require some kind of directional analysis of these signatures, which further require datasets from more than one observatory.
Answer 1: It is doubtless true that association of individual anomalies to earthquakes is not viable; neither the data statistics, nor the underlying physical mechanism of fracturing under stress accumulation allows such correlations. As suggested, we have discussed the anomalous signatures prior to the earthquakes with their azimuth from station and confirmed only the presence of seismo-electromagnetic signatures. Further, as we have only one observatory in the study area, we focused on qualitative analysis of anomalies with events and their azimuth, and have not attempted any quantitative analysis like relation or variability in amplitude of anomalies with the direction of earthquake events. We have modified the manuscript text accordingly.
Comment 2: Whether polarization ratio is calculated for discrete frequencies or for entire frequency range 0.001 to 0.01 Hz. If it is for discrete frequencies, then frequencies need to be mentioned and their variations must be shown for individual frequency. If it is calculated for entire ulf frequency range, then a rational must be given why it is done? I suggest to analysis polarization ratio at different discrete frequencies or small period bands. This would be helpful relating any seismomagnetic signature to depth.
Answer 2: We appreciate the approach suggested by the reviewer. Based on suggestion of reviewer, we have computed the polarization ratios (Z/H and Z/G) in frequency bands as in 0.001-0.002 Hz, 0.002-0.003 …… 0.009-0.01. The anomalies traced from whole frequency band are correspondingly traced in the different frequency bands. For each anomaly, a gradual increase in amplitudes of polarization ratios (PR) are noted in frequency band from 0.001 to 0.006, while gradual or steep decay of PR are noted in frequency band from 0.006 to 0.01. The energy in Z-component is very low due to location of observatory at lower latitude (shown in Figure 4), hence the preference of choosing full frequency range for PR analysis provides significant enhancement in amplitudes for better analysis. Since, we could not find any change in pattern of anomalies from the two approaches, we prefer to compute and analyse the PR in the full frequency range. The PR computed in the full frequency range and in bands 0.001-0.002, 0.006-0.007, and 0.009-0.01 is shown in Figure 1, Figure 2, and Figure 3 respectively.
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AC3: 'Reply on RC3', Rahul Prajapati, 09 May 2024
Status: closed
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RC1: 'Comment on egusphere-2024-177', Anonymous Referee #1, 12 Mar 2024
This paper explores the potential of seismo-electromagnetic emissions in understanding seismic activity and enhancing earthquake monitoring and prediction. The authors analyzed geomagnetic data from the Andaman subduction zone spanning March 2019 to April 2020. They focused on detecting anomalous signatures in the vertical component of the geomagnetic field after eliminating global and seasonal effects. Additionally, they examined polarization ratios derived from spectral density in the ULF range. Over the year-long period, they observed an 80% increase in polarization ratios and 67% deviations in diurnal ratios, occurring approximately 18 days before earthquake events. These enhancements were found to be correlated with 11 out of 14 earthquakes, indicating a success rate of approximately 78% for the study.
Unfortunately the work presents several problems and cannot be published in the present form.
Major problems.
- No discrimination between quiet and disturbed magnetic days. It is known that geomagnetic external perturbations (storms, substorms, bays) produce similar effects on the signal than potential earthquake related anomalies. It is suggested to exclude periods of geomagnetic activity characterized by high values of geomagnetic indices (e.g. Kp, Dst, AE)
- No confutation analysis. The method must be validated considering a comparable period without seismicity to see how the method behave. If the number of anomalies are comparable, the method does not work.
- Range in earthquake magnitudes just limited between 4.5 and 5.3. One would expect that magnitude and distance of earthquake with respect to the geomagnetic station affect the geomagnetic field differently, increasing the amplitude of anomaly with magnitude or with inverse of distance. To have a reliable statistics a large range of magnitudes is necessary. In addition, the work considered 63 earthquakes, then selected 15 “groups” of earthquakes (Figure 8), that were then reduced to 14 (Table 2).
- Lines 178-191. The chosen thresholds (from one sigma to 0.125 sigma, at 0.5 interval of standard deviation) are not robust to detect anomalies. An anomaly should be some signal that clearly emerges from the background. For the chosen thresholds, this is not the case: in this case the anomalies could be simply due to chance.
Minor points
- The sentence from line 12 to line 13 has no verb. I suggest to insert “has been analysed” in line 13, just after “region”.
- Line 15. Please correct “seasonal effects”.
- Line 42. Please delete “been” in “have been studied”.
- Line 54. Please correct “earthquakes”.
- The sentence that starts from line 75 is not clear. There is a list of earthquakes, probably earthquakes occurred before 2000. Therefore, specify it.
- In line 78 the magnitude attributed to the Dec. 26 2004 earthquake is 9.0, while in the next line 83, is attributed as 9.1 Mw.
- Figure 1. The acronym AS (Andaman Trench of the Sumatran Fault System) mentioned in the caption, is not found in the figure. By the way, the caption is poorly written: for instance, it is not clear which geomagnetic station is represented by a triangle (Campbell Bay, Great Nicobar, mentioned in the Data?).
- Line 105. What is “MSL”? mean sea level? Please specify.
- Lines 120-121. The distance is probably taken from earthquakes and geomagnetic station. Please specify.
- List of earthquakes in Table 1. It is evident that no declustering was applied: there are many earthquakes very close in time.
- Line 140. Please correct “indicates”
- Figure 3. Please insert “the anomaly” before “detection”.
- Line 156. The sentence “A ratio >1 indicates the suppression in amplitude of Z-component..” is not clear to me. The ratio is Z/H. Do you mean “…in amplitude of H-component”?
- Line 182. Please delete “is” before “significantly”.
- Line 256. What is “CBY”? Is it the station Campbell Bay? Please specify (of course the first time you introduce the geomagnetic station).
- Line 330. It is introduced the concept of skin depth without any definition or reference.
- Line 334. Please correct “H field”
- Line 344. Please correct “2 months before at stations ESA and MR”
- Line 373. Please write “up to”
- Lines 400-402. Please add some references.
- Line 416, Please write “may facilitate to understand” (delete “to facilitate”)
Citation: https://doi.org/10.5194/egusphere-2024-177-RC1 -
AC1: 'Reply on RC1', Rahul Prajapati, 17 Apr 2024
Dear Editor-in-Chief,
We take this opportunity to thank you, and Referee 1 for thoughtful comments on our manuscript which helped us in improving the manuscript. We hope that the answer of each major and minor comment will meet your expectations. The comments of the reviewers and their replies are listed here one by one, which includes two figures. We request to please go through the attached file in the supplement for figures.
Yours sincerely,
Rahul Prajapati, Kusumita Arora
Reviewer comments # 1
Major comments.
Comment 1. No discrimination between quiet and disturbed magnetic days. It is known that geomagnetic external perturbations (storms, substorms, bays) produce similar effects on the signal than potential earthquake related anomalies. It is suggested to exclude periods of geomagnetic activity characterized by high values of geomagnetic indices (e.g. Kp, Dst, AE)
Answer 1. In the proposed study, we have already selected the anomalies from quiet time by selecting days where kp<3and removed the anomalies correspond to kp>3 (line number 137). Additionally, following the suggestion from the comment, we again compared these anomalous signatures with the DST index for the same duration of study and found that it lies between -50 and +40, which indicates the absence of any storms or substorms (Figure 1). Thus, in the proposed work, the anomalies computed from the vertical component of geomagnetic data are possibly free from the effect of any external origin. We prefer to use only the kp and Dst indices because these indices are computed from lower and middle latitude observatories, and our study also lies in this region only, while the AE index is computed from observatories in the polar region to quantify the geomagnetic activity in the polar region. Thus, we have avoided using the AE index in our study.
Figure 1. The anomalies from vertical component of geomagnetic data (a) diurnal ratio, polarization ratio (b) Z/H, and (c) Z/G, along with geomagnetic indices (d) Kp, and (e) Dst.
Comment 2. No confutation analysis. The method must be validated considering a comparable period without seismicity to see how the method behave. If the number of anomalies are comparable, the method does not work.
Answer 2. Thank you for the point. In this regard, we have tested the same method on the data of the mid-latitude geomagnetic observatory in Hyderabad, India, from March 2019 to March 2020, which has nearly the same duration as the Campbell Bay data. The geomagnetic observatory of Hyderabad is located in Deccan-Shield, which is a completely aseismic zone. The final result we obtained from the Hyderabad data was compared with the final result of the Campbell data, and we noted that in the diurnal ratio, the only anomaly of 28–29 November 2019 partly matches the anomaly of the Hyderabad data from October 22 to November 2, 2019, which is completely absent in the polarisation ratio of Hyderabad. Apart from that, the anomalies in the polarisation ratio of Campbell Bay and Hyderabad are not comparable to any extent. Thus, we believe that the data recorded in the tectonic active region is more likely to record the EM signatures from pre-earthquake processes, and the significant enhancements that appear within an acceptable range of days prior to earthquakes show that the method works well. The comparative figure of the final result of Hyderabad and Campbell data is shown in the below figure.
Figure 2. Diurnal ratio anomalies from vertical component of geomagnetic data (a) Campbell data, (b) Hyderabad data. Polarization ratio anomalies (c), Campbell data (d), Hyderabad data.
Comment 3. Range in earthquake magnitudes just limited between 4.5 and 5.3. One would expect that magnitude and distance of earthquake with respect to the geomagnetic station affect the geomagnetic field differently, increasing the amplitude of anomaly with magnitude or with inverse of distance. To have a reliable statistic a large range of magnitudes is necessary. In addition, the work considered 63 earthquakes, then selected 15 “groups” of earthquakes (Figure 8), that were then reduced to 14 (Table 2).
Answer 3. In the proposed study, from May 2019 to Apr 2020 (duration of study) faces the earthquakes with magnitude range from 4.5 to 5.3 the duration of study. Thus, due to insufficient length of data it was difficult to achieve such objective in present study. The similar type of work is also carried out by Bulusu et al. (2023) and Ida et al. (2012) which supports our study. Bulusu et al. (2023) has identified the anomalous EM signatures (from vertical component of geomagnetic signal) associated with moderate magnitude earthquakes (3.5 ) occurred near to Main Central Thrust (MCT) in Kumaun Himalaya region, India. Similarly, Ida et al. (2012) analysed ULF geomagnetic data at Kashi station, China approximately for four years where several moderate earthquakes occurred within 100-125 km radius of recording station and reported significant changes in vertical component of geomagnetic field prior to the earthquakes.
Figure 8 represents the amplitudes of anomalies of diurnal ratio and polarization ratio correlatable with earthquakes occurring during or after these anomalies. The first dense cluster of 45 earthquakes occurring from end of March 2019 to mid-April 2019 are not included in this figure, as the data length before the occurrence of this cluster is insufficient. The horizontal axis represents earthqaurs or group of earthquakes, which are possibly associated with preceded anomalous signatures instead of whole declustered earthquake from earthquake CatLog.
Comment 4. Lines 178-191. The chosen thresholds (from one sigma to 0.125 sigma, at 0.5 interval of standard deviation) are not robust to detect anomalies. An anomaly should be some signal that clearly emerges from the background. For the chosen thresholds, this is not the case: in this case the anomalies could be simply due to chance.
Answer 4. Han et al. (2015) used threshold value and found a single anomalous signature in vertical component of geomagnetic field prior to two month of Tohoku earthquake M9.0. Similarly, Yousof et al. (2019) used threshold value to identify the anomalous signature in vertical component of geomagnetic field and found a single anomaly two weeks before the Visayas, Philippines earthquake M6.9, 2012. Habora et al. (2004) used threshold condition and identified the anomalous signature in geomagnetic data prior to earthquake occurred on Izu island of magnitude between 6 and 6.5. Habora et al. (2004) also tested threshold condition and noted the isolated anomalies correspond to same earthquakes. Moreover, Arora et al. (2012) analysed the geomagnetic signal of Koyna region to study the anomalous EM signatures from earthquakes occurred due to induced reservoir seismicity with magnitude 2.5 to 4.0 and noted few anomalous signatures in polarization ratio. In this study, Arora et al. (2012) used mean value of polarization ratio by adding 0.27 and 0.72 as a threshold condition to identify the significant variation in polarization ratios.
As the magnitudes of the earthquakes in study duration are moderate (4.5<M<5.3) and occurrence frequency is monthly on an average, it was necessary to lower the thresholds in order to detect the anomalies at all. Also, we have used nighttime data for polarization ratio as well as restricted the values of Kp and Dst indices. Hence we feel that the current thresholds are justified. In Figure 2 above, we see that application of the same thresholds on data from an aseismic site does not produce any anomalies, which further validates our approach.
Minor points:
- The sentence from line 12 to line 13 has no verb. I suggest to insert “has been analysed” in line 13, just after “region”.
Answer: Revised (line number 13)
- Line 15. Please correct “seasonal effects”.
Answer: Corrected ((line number 13)
- Line 42. Please delete “been” in “have been studied”.
Answer: corrected ((line number 42)
- Line 54. Please correct “earthquakes”.
Answer: Corrected ((line number 54)
- The sentence that starts from line 75 is not clear. There is a list of earthquakes, probably earthquakes occurred before 2000. Therefore, specify it.
Answer: Sentence revised ((line number 74-78)
- In line 78 the magnitude attributed to the Dec. 26 2004 earthquake is 9.0, while in the next line 83, is attributed as 9.1 Mw.
Answer: Corrected ((line number 83)
- Figure 1. The acronym AS (Andaman Trench of the Sumatran Fault System) mentioned in the caption, is not found in the figure. By the way, the caption is poorly written: for instance, it is not clear which geomagnetic station is represented by a triangle (Campbell Bay, Great Nicobar, mentioned in the Data?).
Answer: Figure 1 is replaced by revised figure including the correction of AS by AT. The figure caption is also revised (Page No. 5).
- Line 105. What is “MSL”? mean sea level? Please specify.
Answer: The sentence is revised by specifying the MSL as mean sea level ((line number 106).
- Lines 120-121. The distance is probably taken from earthquakes and geomagnetic station. Please specify.
Answer: Sentence is revised (line 123)
- List of earthquakes in Table 1. It is evident that no declustering was applied: there are many earthquakes very close in time.
Answer: Table 1 showing the all earthquakes available in ISC CatLog, while Table 2 showing the declustured earthquakes with details of preceding anomalies or possible EM signature from pre-earthquake processes.
- Line 140. Please correct “indicates”
Answer: Corrected ((line number 142)
- Figure 3. Please insert “the anomaly” before “detection” ((line number 149-150).
Answer: Revised
- Line 156. The sentence “A ratio >1 indicates the suppression in amplitude of Z-component.” is not clear to me. The ratio is Z/H. Do you mean “…in amplitude of H-component”?
Answer: in this section we discussed about diurnal ratio i.e. ratio of regular diurnal and daily diurnal. The regular diurnal constructed from best quiet days of each month, by taking the ratio the background signal in daily diurnal is minimised and close to 1. But if there is small amplitude of diurnal field (due to superimpose of other field) the ratio will be greater than 1. Thus from time series of ratio of regular and daily diurnal ratio, it is easy to identify the anomalous Z-field by tracing the ratio greater than 1.
- Line 182. Please delete “is” before “significantly”.
Answer: Corrected
- Line 256. What is “CBY”? Is it the station Campbell Bay? Please specify (of course the first time you introduce the geomagnetic station).
Answer: Sentence is revised (line 258).
- Line 330. It is introduced the concept of skin depth without any definition or reference.
Answer: Sentence is revised (line 332-333).
- Line 334. Please correct “H field”
Answer: Corrected ((line number 337)
- Line 344. Please correct “2 months before at stations ESA and MR”
Answer: Sentence revised ((line number 347-348)
- Line 373. Please write “up to”
Answer: sentence revised (line 377)
- Lines 400-402. Please add some references.
Answer: Sentence is revised and reference added ((line number 404-406).
- Line 416, Please write “may facilitate to understand” (delete “to facilitate”)
Answer: Sentence is corrected (line number 420).
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RC2: 'Comment on egusphere-2024-177', Anonymous Referee #2, 12 Apr 2024
In this investigation, the author attempts to correlate ULF geomagnetic anomalies to 63 seismic activities occurred within 250 km from the observatory site during 2019 to 2020. To identify geomagnetic anomalies associated with lithospheric processes, three approaches have been utilized: diurnal ratio, polarization ratio I SZ/SH and II SZ/SG. The results have presented that geomagnetic anomalies appear before the large percent of earthquakes.
However, there are still some major or minor unclear issues:
- There are some grammar or express mistakes but it is not easy to point them out because there is no line number in the manuscript.
- In Figure 1, there are some earthquakes and related numbers added together and it is no easy to figure out and the resolution is also not enough, including Figure 3.
- It is maybe better for Table 1 acting as an appendix?
- We find no more useful information in Figure 2, or it can be compared with that of raw data.
Citation: https://doi.org/10.5194/egusphere-2024-177-RC2 -
AC2: 'Reply on RC2', Rahul Prajapati, 22 Apr 2024
Dear Editor-in-Chief,
We take this opportunity to thank you, and referee 1 for thoughtful comments on our manuscript which helped us in improving the manuscript. We hope that the answer of each major and minor comments will meet your expectations. the figure discussed in text of reply is included in pdf file attached in spplement section, so please refer to attached file also. In attached pdf, the comments of the reviewers are shown in red color, our reply in normal font and black color.
Yours sincerely,
Rahul Prajapati, Kusumita Arora
Reviewer comments # 2
Minor and Major comments.
Comment 1. There are some grammar or expression mistakes but it is not easy to point them out because there is no line number in the manuscript.
Answer 1. We have thoroughly checked and revised sentences and corrected grammar mistakes in the manuscript according to suggestions of reviewer.
Comment 2. In Figure 1, there are some earthquakes and related numbers added together and it is no easy to figure out and the resolution is also not enough, including Figure 3.
Answer 2. A swarm of earthquakes (numbered from 1 to 45) occurs at the beginning of the study period. These earthquakes are concentrated in a very small area and representative circles overlap each other. Thus it is difficult to resolve the earthquakes and their numbers separately. The resolution of the original figure was good and its size was 23672 kb. We are again uploading the high resolution figures of 1 and 3 in supplementary section for your kind review. An enlarged view of the earthquake cluster area is additionally shown here Figure S.
Figure S. Enlarge view of earthquake event clustered region shown in rectangle of figure 1.
Figure 1. Bathymetry map of Andaman-Nicobar subduction zone (modified after Cochran et al., 2010; E. Anusha et al., 2020). The faults are AT (the Andaman Trench of the); SS (the Seulimeum strand); WAF (the West Andaman Fault) of Sumatran Fault System. The green, pink, and red circles are the earthquakes are associated with AT, WAF, and SS faults respectively. the location of Campbell Bay geomagnetic station shown by triangle.
Figure 3. Schematics of work flow of diurnal ratio and polarization approach in the anomaly detection of EM signature in ULF range.
Comment 3. It is maybe better for Table 1 acting as an appendix?
Answer 3. We have analysed our results in the Result and Discussion sections with reference to earthquakes by its number only, which is mentioned in Table 1. Thus we believe that Table 1 should be included in the manuscript.
Comment 4. We find no more useful information in Figure 2, or it can be compared with that of raw data.
Answer 4. The purpose of including the figure 2 is to demonstrate the quality of data and data gaps. Figure 2 shows clearly the quality of data and its availability is enough good for further processing to meet our objectives. The raw data will again show same information and its comparison with present data (shown in figure 2) will not give any additional information. Thus, we believe that inclusion of figure 2 in the present form is appropriate.
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RC3: 'Comment on egusphere-2024-177', Anonymous Referee #3, 02 May 2024
The paper is about identification of seismo-electromagnetic anomaly as an earthquake precursor from the geomagnetic field time series recorded using digital fluxgate magnetometers at an observatory. Earthquakes occurring around 250 Km radius of this observatory are considered for their precursory signature. Analysis of data is presented through two methods namely diurnal ratio and polarization ratio. In the diurnal ratio method authors have considered hourly mean, thereby filtering high frequency variations and considered mean from quiet day variation for defining diurnal ratio. Similarly, for polarization analysis local night time data is utilized and polarization ratio (SZ/SH and SZ/SG) is calculated. For the calculation authors have used frequency band from 0.001 to 0.01 Hz. Amplitude variation beyond μ + 0.25σ for diurnal ratio and beyond μ + 0.5σ for polarization ratio is considered as anomalous variation.
The major problem is considered amplitude anomalies are correlated with individual or group of earthquakes of different magnitude, earthquakes from different epicentral distances, earthquakes from different depth. How an amplitude anomaly is giving directional indications? Further it is not clear how the variation of earthquake parameters are affecting identified anomaly. I suggest rather than associating anomalies to particular earthquake, it would be better to say that there exist seismo-magnetic anomalies in the data but relating it with particular earthquake require some kind of directional analysis of these signatures, which further require datasets from more than one observatory.
Whether polarization ratio is calculated for discrete frequencies or for entire frequency range 0.001 to 0.01 Hz. If it is for discrete frequencies, then frequencies need to be mentioned and their variations must be shown for individual frequency. If it is calculated for entire ulf frequency range, then a rational must be given why it is done? I suggest to analysis polarization ratio at different discrete frequencies or small period bands. This would be helpful relating any seismomagnetic signature to depth.
In light of above I suggest a revision of the paper. However, I appreciate authors effort in this field of study, which is still in infancy and require enormous amount of data.
Citation: https://doi.org/10.5194/egusphere-2024-177-RC3 -
AC3: 'Reply on RC3', Rahul Prajapati, 09 May 2024
Dear Editor-in-Chief,
We take this opportunity to thank you, and referee 3 for thoughtful comments on our manuscript which helped us in improving the manuscript. We hope that the answers to each major and minor comment will meet your expectations. The figure discussed in the text of the reply is included in pdf file attached in supplement section, so please refer to the attached file also. In the attached pdf, the comments of the reviewers are shown in red color, and our reply in normal font and black color.
Yours sincerely,
Rahul Prajapati, Kusumita Arora
Reviewer comments # 3
Comment 1: The major problem is considered amplitude anomalies are correlated with individual or group of earthquakes of different magnitude, earthquakes from different epicentral distances, earthquakes from different depth. How an amplitude anomaly is giving directional indications? Further it is not clear how the variation of earthquake parameters are affecting identified anomaly. I suggest rather than associating anomalies to particular earthquake, it would be better to say that there exist seismo-magnetic anomalies in the data but relating it with particular earthquake require some kind of directional analysis of these signatures, which further require datasets from more than one observatory.
Answer 1: It is doubtless true that association of individual anomalies to earthquakes is not viable; neither the data statistics, nor the underlying physical mechanism of fracturing under stress accumulation allows such correlations. As suggested, we have discussed the anomalous signatures prior to the earthquakes with their azimuth from station and confirmed only the presence of seismo-electromagnetic signatures. Further, as we have only one observatory in the study area, we focused on qualitative analysis of anomalies with events and their azimuth, and have not attempted any quantitative analysis like relation or variability in amplitude of anomalies with the direction of earthquake events. We have modified the manuscript text accordingly.
Comment 2: Whether polarization ratio is calculated for discrete frequencies or for entire frequency range 0.001 to 0.01 Hz. If it is for discrete frequencies, then frequencies need to be mentioned and their variations must be shown for individual frequency. If it is calculated for entire ulf frequency range, then a rational must be given why it is done? I suggest to analysis polarization ratio at different discrete frequencies or small period bands. This would be helpful relating any seismomagnetic signature to depth.
Answer 2: We appreciate the approach suggested by the reviewer. Based on suggestion of reviewer, we have computed the polarization ratios (Z/H and Z/G) in frequency bands as in 0.001-0.002 Hz, 0.002-0.003 …… 0.009-0.01. The anomalies traced from whole frequency band are correspondingly traced in the different frequency bands. For each anomaly, a gradual increase in amplitudes of polarization ratios (PR) are noted in frequency band from 0.001 to 0.006, while gradual or steep decay of PR are noted in frequency band from 0.006 to 0.01. The energy in Z-component is very low due to location of observatory at lower latitude (shown in Figure 4), hence the preference of choosing full frequency range for PR analysis provides significant enhancement in amplitudes for better analysis. Since, we could not find any change in pattern of anomalies from the two approaches, we prefer to compute and analyse the PR in the full frequency range. The PR computed in the full frequency range and in bands 0.001-0.002, 0.006-0.007, and 0.009-0.01 is shown in Figure 1, Figure 2, and Figure 3 respectively.
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AC3: 'Reply on RC3', Rahul Prajapati, 09 May 2024
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