the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Rescue, Integration, and Analytical Application of historical data from eight pioneering geomagnetic observatories in China
Abstract. Decades to centuries of continuous geomagnetic observation data have extensive scientific research and practical application value, especially in revealing the long-term variation rules of the geomagnetic field, which is irreplaceable. During the International Geophysical Year (1957–1958), China established geomagnetic observatories in Beijing, Lhasa, Lanzhou, Wuhan, Guangzhou, Changchun, and Urumqi, forming the initial structure of China's geomagnetic observation network together with the Shanghai Observatory. These observatories have continuously observed despite facing many challenges since their establishment, accumulating a large amount of valuable observational data, making significant contributions to the progress of geomagnetic scientific research and development. However, the scattered storage state of these historical data and the potential risk of damage pose a threat to the integrity and reliability of the data. This study conducted a rescue integration of the historical observational data from eight pioneering geomagnetic observatories in China, significantly improving data quality and facilitating long-term preservation and use of the data. This article introduces the basic conditions of eight observatories, including their locations, changes in location, observation environments, magnetic rooms, the magnetism of building materials, the layout of building facilities, measuring instruments, etc. These are the main prerequisites and foundations for ensuring the quality of observation data. Then, it introduces the integration and processing of historical data, including data collection, digitization, unification of formats, anomaly detection, and processing. Subsequently, the processed data were validated, including assessments of daily variations accuracy and long-term stability. The results show that the quality of the integrated historical data has been significantly improved. These datasets are of great value for improving historical geomagnetic field models, studying variable fields, main geomagnetic fields, and their long-term variations. Finally, we applied the data to the analysis and research of Sq and geomagnetic jerks, exploring the spatiotemporal variation characteristics of Sq and jerk in the China. Sq is mainly a daytime phenomenon, and its variation pattern in the middle and low latitude regions is mainly characterized by its dependence on latitude and local time. The geomagnetic jerk phenomenon exhibits significant regional differences and asynchronous occurrence times of jerks. Jerk events in 1969, 1979, 1991, 2003, and 2019 were observed at all observatories and had distinct jerk variation characteristics. Other jerks were only observed at some observatories or individual observatories. The maximum time difference for the occurrence of the same jerk event at different observatories was 2 years. This study aims to provide these precious datasets to the scientific community and the public so that these data can be integrated with data from other sources, thereby further exploring the spatiotemporal evolution and physical mechanisms of the geomagnetic field. The historical datasets of the eight geomagnetic observatories that have been integrated and quality controlled are available at https://doi.org/10.5281/zenodo.14560950 (Zhang et al., 2024b).
- Preprint
(1637 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 17 May 2025)
-
RC1: 'Comment on essd-2025-6', Anonymous Referee #1, 17 Mar 2025
reply
It is obvious that the authors of this work have accomplished a very valuable and meaningful task. Scientists working on related research can utilize results of this work for in-depth studies. I strongly recommend publishing it as soon as possible.
But for publication, the manuscript needs several minor modifications. The specific suggestions are as follows:
1. The titles of Section 2.1.7 & 2.1.8 not match the content, and need to be modified.
2. Why was the data after 2022 not processed, and what’s the reason? Please briefly explain in the article.
3. In Figure 6 on page 19, the unit of Local Time should be labeled.Citation: https://doi.org/10.5194/essd-2025-6-RC1 -
AC1: 'Reply on RC1', Suqin Zhang, 20 Mar 2025
reply
Dear Reviewer,
Thank you very much for your positive feedback and constructive suggestions on our manuscript. We greatly appreciate your time and effort in reviewing our work. We have carefully addressed your comments and made the necessary revisions to improve the manuscript. Below are our responses to your specific suggestions:
- **Regarding the titles of Section 2.1.7 & 2.1.8**:
We agree with your observation that the titles did not fully match the content. We have revised the titles to better reflect the content of these sections.
- **Regarding the data after 2022**:
We apologize for not clarifying this point in the original manuscript. The data after 2022 was not included because it was incomplete at the time of our analysis. We have added a brief explanation in Section 2.3 to address this issue.
- **Regarding Figure 6 on page 19**:
We thank you for pointing out the missing unit for Local Time in Figure 6. We have now labeled the unit clearly in the revised figure to avoid any confusion.
Thank you again for your valuable feedback.
Sincerely,
Suqin Zhang
On behalf of all authors
Citation: https://doi.org/10.5194/essd-2025-6-AC1
-
AC1: 'Reply on RC1', Suqin Zhang, 20 Mar 2025
reply
-
CC1: 'Comment on essd-2025-6', Xin Changjiang, 01 Apr 2025
reply
The continuous, complete, accurate and reliable geomagnetic field data highlights its value. With the development of technology, the observation data of some prestigious geomagnetic observatories have almost experienced the process from analog to digital observation, and the processing and storage of the data have taken a different way, especially for some data stored in paper and floppy disk, there is a serious risk of loss as time goes by. This paper introduces the observation of China's eight pioneering geomagnetic observatories, describes detailedly the complete process of data collection, digitization and standardization of analog data, data processing and quality control, and verifies the reliability of data by comparing and correcting the daily variation accuracy and secular variation stability, and applies the data to the analysis of different geomagnetic phenomena. It further embodies the important significance of rescuing and integrating the historical data of geomagnetic observatories. The examples in this paper are appropriate and clear, the words, formulas, symbols are accurate, and the ICONS are standard. The research method is feasible, the idea is clear and the conclusion is reliable, which has important guiding significance for the data rescue, data processing, quality control and analysis application of geomagnetic observatories.
Citation: https://doi.org/10.5194/essd-2025-6-CC1 -
AC2: 'Reply on CC1', Suqin Zhang, 09 Apr 2025
reply
Thank you for your positive feedback on our paper. We are pleased to hear that our work on the geomagnetic observatories' data rescue and integration is valued.
Citation: https://doi.org/10.5194/essd-2025-6-AC2
-
AC2: 'Reply on CC1', Suqin Zhang, 09 Apr 2025
reply
-
CC2: 'Comment on essd-2025-6', Z.H. He, 16 Apr 2025
reply
Line 213: The author has misplaced the Section 2.1.7 Lhasa Observatory (IAGA code LSA) to the Line 203 Section 2.1.6 Lhasa Observatory (IAGA code LSA).
Line 223: And the similar mistake in 2.1.8 Lhasa Observatory (IAGA code LSA).
They should be corrected.
Citation: https://doi.org/10.5194/essd-2025-6-CC2
Data sets
An integrated and quality-controlled historical datasets of eight pioneering geomagnetic observatories in China S. Q. Zhang et al. https://doi.org/10.5281/zenodo.14560950
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
168 | 28 | 8 | 204 | 9 | 7 |
- HTML: 168
- PDF: 28
- XML: 8
- Total: 204
- BibTeX: 9
- EndNote: 7
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1