## 5 Conclusions
; funding acquisition, K.Z., D.M. and A.D.S. All authors have read and agreed to the published version of the manuscript. **Funding:** This research was funded by the National Natural Science Foundation of China, grant number 41974084; the China Postdoctoral Science Foundation, grant number 2021M691190; the Italian Space Agency, grant number 2020-32-HH.0 (Limadou-Science+); the International Cooperation Project of the Department of Science and Technology of Jilin Province, grant number 20200801036 GH; and the Italian Ministry of University and Research, grant number D53J19000170001 (Pianeta Dinamico--Working Earth). **Data Availability Statement:** The _Swarm_ satellite data are freely available from ftp and http servers (swarm-dis.e.oesa.int, last accessed on 3 January 2022). The USGS Earthquake catalog is freely accessible at [[https://earthquake.usgs.gov/earthquakes/map](https://earthquake.usgs.gov/earthquakes/map)]([https://earthquake.usgs.gov/earthquakes/map](https://earthquake.usgs.gov/earthquakes/map)) (accessed on 1 February 2022). **Acknowledgments:** We warmly thank [PERSON] for the software developed to analyze the _Swarm_ data, and we would like to acknowledge [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON], who participated in some of the discussions about this work and its previous investigations carried out in the framework of the SAFE (SwArm For Earthquake study) ESA-funded project and in the following activities and projects. **Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Appendix A Evaluation of the Declustering of the Earthquake Catalog on the Worldwide Statistical Correlation Results  
This appendix is dedicated to evaluating how the decluster technique that was used to pre-process the earthquake catalog could have affected the results. Determining if an earthquake is an isolated event or part of a seismic swarm or sequence--and, in this last case, discriminating between foreshocks, mainshocks, and aftershocks--has been always a very challenging topic for seismologists [53]. Very recent frontiers of seismology are even trying to evaluate in real-time if an earthquake is a foreshock or a mainshock by a traffic-light scheme based on the evaluation of the \(b\)-value of the Gutenberg-Richter distribution [54]. Declustering an earthquake catalog means the removal of the foreshocks and aftershocks in order to identify the \"clusters\" of seismicity led by the mainshock. The detection of the cluster is a difficult problem, and several approaches are available, such as that of [PERSON] [35] that we applied in this paper, which uses a radius around the event (a radius of 10 km for the present paper) and a time window to search for foreshocks (with 10 days in advance, for this paper) and aftershocks (in this paper: 20 days). If another earthquake is detected inside the space-time researched area, the same approach is applied until no other events are detected. The algorithm also takes into account the uncertainty of the earthquake localization that we selected from the values directly available in the USGS catalog. A different choice of such free parameters of the algorithm yields obviously different results. For example, in [PERSON] et al. [29], a shorter time window was used (1 day before and 10 days after), but we found that some events that occurred in the same tectonic context in a short time were not detected as the same cluster for such strict time windows; therefore, in the present work, we decided to use a slightly longer time window.