Magnetic Anomaly and Hypocenter Temperature Structure Dataset in Eastern Margin of
QinghaiTibet Plateau
Wang, J.^{1}^{*}Zhang, G. W.^{1 }Liang, S. S.^{2}
1. Institute of Crustal Dynamics, China Earthquake Administration, Beijing 100085, China;
2. China Earthquake Network Center, Beijing 100045, China
Abstract:The eastern margin of the QinghaiTibet Plateau is one of the most complex and intense seismic activity areas in China. Temperature is one of the key factors that indicate the brittleplastic deformation and seismogenic layer depths distribution. Based on 6,406 seismic data records from the eastern margin of the QinghaiTibet Plateau, the 4,921 of them with magnitudes M≥2.0 during 20082017 were relocated by using two crustal velocity models and the doubledifference relocation algorithm. Curiepoint depths were estimated from NGDC720 magnetic anomaly. Crustal temperature structures were then calculated by incorporating surface heat flow and Curiepoint depths based on the 1D steady thermal conduction equation. The dataset consists of five Excel files: (1) earthquake relocations with magnitudes M≥2.0 in the eastern margin of the QinghaiTibet Plateau during 20082017, including 4,540 earthquakes with 2.0≤M<4.0, and 381 earthquakes with M≥4.0; (2) total and x, y, zdirection vector of NGDC720 magnetic anomalies observed at 0 km; (3) xy, xz, yz, zzdirection gradient tensor of the NGDC720 magnetic anomalies observed at 10 km; (4) Curiepoint depths and average temperature gradients of the magnetic layer; and (5) crustal temperature structures for hypocenters. The dataset is archived in .xlsx format with data size of 15.9 MB (Compressed to one file, 15.3 MB). The research paper based on the dataset was published at Chinese Journal of Geophysics, Vol. 61, No. 5, 2018.
Keywords:earthquake relocation; NGDC720 magnetic anomaly; Curiepoint depth; crustal temperature structure; QinghaiTibet Plateau
1 Introduction
The eastern margin of QinghaiTibet Plateau is one of the most intense and complex seismic activity regions in China. Since the 2008 Wenchuan Ms8.0 earthquake, there have occurred four large earthquakes with the Magnitude (M) no less than 6.5 in this area^{[}^{1–4]}. Temperature is one of the key factors to control the lithospheric brittleplastic deformation, which further constrains the depth of the seismogenic layer. Due to that the surface heat flow measurements in the eastern margin of the QinghaiTibet Plateau are mainly distributed in the Sichuan Basin, large measurement gaps covers the regions in to the west of the Longmenshan and Xianshuihe faults with strong seismic activities. Therefore, it is difficult to study the relationship between crustal temperature structure and seismicity in the whole region of the eastern margin of the QinghaiTibet Plateau effectively. Curiepoint depths obtained from inversion of magnetic anomaly data can be used to study the temperature structure of deep crust.
This paper employed the doubledifference location method^{[5]} to relocate the earthquakes occurring in the eastern margin of the QinghaiTibet Plateau with M≥2.0 during 20082017. Curiepoint depths were estimated from NGDC720 magnetic anomaly. Crustal temperature structures were then calculated by incorporating surface heat flow and Curiepoints depths based on 1D steady thermal conduction equation. Finally, the hypocenter temperatures were calculated and their geodynamic implications were discussed.
2 Metadata of Dataset
The metadata for the magnetic anomaly and hypocenter temperature structure dataset in eastern margin of QinghaiTibet Plateau ^{[6]} is summarized in Table 1, including the name, authors, geographical region, data files, data publisher and data sharing policy, etc.
Table 1 Metadata of magnetic anomalies and temperature structures dataset in the eastern margin of Tibetan Plateau
Items

Description

Dataset full name

Magnetic anomaly and hypocenter temperature structure dataset in eastern margin of QinghaiTibet Plateau

Dataset short name

MagneticAnomalyTemStr_E.Tibet

Authors

Wang, J. R55592019, Institute of Crustal Dynamics, China Earthquake Administration, wangjianhydz@163.com
Zhang, G. W. R56082019, Institute of Crustal Dynamics, China Earthquake Administration, jluaaa@163.com
Li, C. F. Department of Marine Sciences, Zhejiang University;Laboratory of Marine Mineral Resources??Qingdao National Laboratory for Marine Science and Technology,
Liang, S. S. R62882019, China Earthquake Network Center, liangshanshan@seis.ac.cn

Geographical region

Eastern margin of the QinghaiTibet Plateau

Year

20082017

Data format

.kmz, .shp, .xlsx

Data size

15.3 MB (after compression)

Data files

The dataset consists of 1 compressed data file package, including 3 data folders, 32 data files:
(1) earthquake relocations with magnitudes M≥2.0 in the eastern margin of the QinghaiTibet Plateau during 20082017, including 4,540 earthquakes with 2.0≤M<4.0 and 381 earthquakes with M≥4.0;
(2) total and x, y, zdirection vector of NGDC720 magnetic anomalies observed at 0 km;
(3) xy, xz,yz, zzdirection gradient tensor of NGDC720 magnetic anomalies observed at 10 km;
(4) Curiepoint depths and average temperature gradients of the magnetic layer;
(5) crustal temperature structures for hypocenters.

Foundations

China Earthquake Administration (ZDJ201909); National Natural Science Foundation of China (41704086, 41776057)

Data publisher

Global Change Research Data Publishing & Repository http://www.geodoi.ac.cn

Address

No. 11A Datun Road, Chaoyang District, Beijing 100101, China

(To be continued on the next page)
(Continued)
Item

Description

Data sharing policy

Data from the Global Change Research Data Publishing & Repository includes metadata, datasets (data products), and publications (in this case, in the Journal ofGlobal Change Data & Discovery). Data sharing policy includes: (1) Data are openly available and can be free downloaded via the Internet; (2) End users are encouraged to use Data subject to citation; (3) Users, who are by definition also valueadded service providers, are welcome to redistribute Data subject to written permission from the GCdataPR Editorial Office and the issuance of a Data redistribution license, and; (4) If Data are used to compile new datasets, the ‘ten percent principal’ should be followed such that Data records utilized should not surpass 10% of the new dataset contents, while sources should be clearly noted in suitable places in the new dataset^{[4]}

Communication and Searchable System

DOI, DCI, CSCD, WDS/ISC, GEOSS, China GEOSS

3 Method
3.1 Data Source
The earthquake data with M≥2.0 in the eastern margin of the QinghaiTibet Plateau during 20082017 used in the relocation were obtained from the China Earthquake Network Center. NGDC720 magnetic anomaly was acquired from the National Geophysical Data Center of the United States (https://www.ngdc.noaa.gov/). The magnetic data was constructed from the magnetic anomaly model EMAG2 and the satellite magnetic anomaly model MF6 to construct a global 720order spherical harmonic magnetic anomaly model, which can calculate the threecomponent magnetic anomalies at different observed altitudes at any latitude and longitude. Therefore, it has broad application value^{[}^{8]}.
3.2 Methodology
3.2.1 Earthquake Relocation Algorithm
Doubledifference relocation method is a relative earthquake location method, and its basic principle is as follows^{[5]}: If the distance between two earthquake sources is smaller than the distance between event and station, and the scale of velocity heterogeneity, then the ray paths of the hypocenter and this station are almost the same. Because the source of absolute error for different events is the same, the ray path is only different in a small area near the hypocenter. Therefore, the traveltime difference between two events observed at a common station can be considered as a spatial offset between the two events. This method can eliminate effectively the location errors caused by the lateral inhomogeneity of crustal velocity structure.
Assuming that the two events i and j are close to each other, then the traveltime difference observed by station k and the residual error when calculating it, i.e., the doubledifference drij k is calculated as follows:
(1)
Whereti k and tj k are the traveltime of the events i and j for the station k, respectively.obs and cal indicate the observed and calculated travel times, respectively. Combining all hypocentral pairs for a station, and for all stations to form a linear equation system
(2)
Where G defines a matrix with the size of M×4N (M, number of doubledifference observations; N, number of events), m is the variation in hypocentral parameters, d is the data vector in Eq. (1), W is a diagonal matrix to weight each equation. Damped least squares can be constructed by applying conjugate gradient method on Eq. (2)^{[}^{5]}.
3.2.2 NGDC720 Magnetic Anomalies and Their Gradient Tensors
The Earth’s geomagnetic field potential function can be written in a spherical harmonic series ^{[9]}
(3)
Where a is the Earth’s radius (6,371.2 km), r is he geocentric coordinates (km), θ and λ are the colatitude and longitude (°), respectively. gm n and hm n are called the Gauss coefficients, and Pm n(cosθ)is the Schmidt quasinormalized form of associated Legendre function of degree n and order m. The threevector components of the geomagnetic field can be obtained from:
(4)
Where N=720; F_{x}, F_{y}, and F_{z} are the x, y, zdirection vector of magnetic anomaly. The total magnetic anomaly can be calculated by , and the gradient tensor F_{GT} can be derived from:
(5)
3.2.3 Curiepoint Depth Estimation
Assuming infinite horizontal extensions of magnetic sources, the radially averaged amplitudes spectrum of the total field magnetic anomaly can be expressed as^{[}^{9]}:
(6)
Where and are the radially averaged amplitude spectra of the total field magnetic anomaly and magnetization, respectively. B is a constant. Z_{t} and Z_{b} are the depths to the top and bottom of the magnetic sources, respectively. k is the wavenumber. In the case of fractal magnetization, the following relation is established:
(7)
Where β is the fractal exponent for the 3D magnetization. Substituting Eq. (7) into Eq. (6) and taking natural logarithm on both sides, we can get:
(8)
Where C is a constant. Eq. (8) can be simplified at middle to highwavenumber band to
(9)
Where D is a constant and at lowwavenumber band to
(10)
Where E is a constant and Z_{0} is the centroid depth of the magnetic source.Z_{t} and Z_{0} can be estimated by leastsquare linear fitting at middle to highwavenumber and lowwavenumber bands based on Eqs. (9) and (10), respectively. Z_{b} can be estimated by
(11)
3.2.4 Crustal Temperature Structure
Assuming a continuous heat production in the lithosphere that decreases exponentially with depth, the 1D steady heat conduction equation is
(12)
where T is the temperature (??), z is the depth (km), k is the thermal conductivity (W/(m??)), H_{0} is the heat production rate at the surface (μW/m^{3)}, and h_{r} is the characteristic dropoff of heat production (km). Integrating Eq. (12) we can get:
(13)
Assuming that the temperature at the surface Z_{0} is T_{0} and the temperature T_{c} is at the depth ofZ_{b}, then
(14)
3.3 Technology Roadmap
Firstly, we relocated the original earthquake catalogue by the doubledifference location method^{[}^{5]}. Secondly, we calculated NGDC720 threecomponent geomagnetic anomaly, total field magnetic anomaly, and gradient tensors. Thirdly, we estimated Curiepoint depth according to 3d fractal magnetization model, and calculated crustal temperatures using the thermal conductivity changes with temperature. Finally, we analyzed and discussed the relationship between the crustal temperature structure and seismicity. The specific technical route is shown in Figure 1.
Figure 1 Data development technology roadmap
4 Results and Validation
4.1 Dataset Composition
Magnetic anomaly and hypocenter temperature structure dataset in eastern margin of QinghaiTibet Plateau includes:
(1) Earthquake relocations with magnitudes M≥2.0 in the eastern margin of the QinghaiTibet Plateau during 20082017, including 4,540 earthquakes with 2.0≤M≤4.0 and 381 earthquakes with M>4.0: RelocatedEarthquakes.xlsx.
(2) Total and threecomponent vectors of NGDC720 magnetic anomalies observed at 0 km: MagneticAnomaly_ NGDC720.xlsx.
(3) Gradient tensors of NGDC720 magnetic anomalies observed at 10 km: GradientTensor_NGDC720.xlsx.
(4) Curiepoint depths and average temperature gradients of the magnetic layer: CurieDepth_ Tem.Gra dient.xlsx.
(5) Crustal temperature structures for hypocenters: Tem.Structure.xlsx.
4.2 Dataset Validation
We calculated average temperature gradient of the magnetic layer in the eastern margin of the QinghaiTibet Plateau. Most regions show distinct low geothermal gradient (<20 ^{o}C /km). Drilling data of the Sichuan Basin show that the geothermal gradient is about 17.733.3 ??/km with an average of about 22.8 ??/km^{[12]}, indicating that the average geothermal gradient of the magnetic layer in the eastern margin of the QinghaiTibet Plateau estimated in this study is in line with the actual geological settings. The crustal temperature parameters (k=3.39W/(m ^{o}C), h_{r}=8.684 km, and H_{0}=2.08 μW/m^{3}) obtained by using the least square fitting (Figure 2) are consistent with those measured in the laboratory^{[12–13]}. The hypocenter temperatures of the 2008 Wenchuan Ms8.0, 2013 Lushan Ms7.0, 2013 Minxian Ms6.6, 2014 Ludian Ms6.5 and 2017 Jiuzhaigou Ms7.0 are almost around 300??, indicating that these earthquakes occurred in the crustal brittleplastic deformation transition zone (Figure 3).
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Figure 2 Correlation between surface heat flow (Q_{s}) and Curiepoint depths (Z_{b}).
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Table 2 Relocation of M≥6.5 earthquakes in the eastern margin of the QinghaiTibet Plateau^{[11]}
Earthquake

Longitude (°E)

Latitude (°N)

Depth (km)

Compared depth (km)

2013 Lushan Ms7.0

102.971,0

30.298,3

19.5

17.8^{[1]}

2013 Minxian Ms6.6

104.211,7

34.546,9

13.0

13.5^{[2]}

2014 Ludian Ms6.5

103.330,1

27.115,5

13.5

15.0^{[3]}

2017 Jiuzhaigou Ms7.0

103.837,6

33.165,5

15.9

16.9^{[4]}

Figure 3 Magnetic anomalies and gradient tensors, crustal temperature structures and distribution of relocated focal depths along four profile AA’ (a and b), BB’ (c and d), CC’ (e and f) and DD’ (g and h)
5 Discussion and Conclusion
The magnetic anomaly and hypocenter temperature structure dataset in Eastern Margin of QinghaiTibet Plateau includes the accurate relocation of 4,921 earthquakes with in the eastern margin of the QinghaiTibet Plateau from 2008 to 2017 obtained by using two different crustal velocity models according to the doubledifference relocation algorithm. The depths of relocated earthquakes domain 520 km. The dataset contains three components and total field and gradient tensor magnetic anomalies based on the NGDC720 geomagnetic model. Most earthquakes occurred in the negative or strong/weak magnetic anomaly domains. The gradient tensor magnetic anomalies can identify the locations with intense seismicity better, especially with large earthquakes, than those on the vector and total field anomaly maps. In addition to the 2013 Minxian Ms6.6 earthquake, the other four earthquakes with M≥6.5 all occurred in regions with large Curie depths and low geothermal gradients. The crustal temperature structures indicate that most M≥2.0 earthquakes in the eastern margin of the QinghaiTibet Plateau occurred at temperature of 100500 ??, and most M≥4.0 earthquakes occurred at temperature of 200400 ^{o}C. The 2008 Wenchuan Ms8.0, 2013 Minxian Ms6.6, 2014 Ludian Ms6.5 and 2017 Jiuzhaigou Ms7.0 earthquakes all occurred at about 300 ^{o}C, while the 2013 Lushan Ms7.0 earthquake occurred at nearly 400 ^{o}C, which was related to local tectonic stress anomalies.
Author Contributions
Wang, J. designed the dataset and completed the manuscript. Zhang, G. W. and Liang, S. S. collected data for the earthquake relocations. We would like to thank Prof. Li C. F. in Zhejiang University for the constructive suggestion on the validation of the dataset.
References
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