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Time correction of the ocean bottom seismometers deployed at the southwest Indian ridge using ambient noise cross-correlation 被引量:5

Time correction of the ocean bottom seismometers deployed at the southwest Indian ridge using ambient noise cross-correlation
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摘要 Seismic monitoring using ocean bottom seismometers(OBS) is an efficient method for investigating earthquakes in mid-ocean ridge far away from land. Clock synchronization among the OBSs is difficult without direct communication because electromagnetic signals cannot propagate efficiently in water. Time correction can be estimated through global positioning system(GPS) synchronization if clock drift is linear before and after the deployment. However, some OBSs in the experiments at the southwest Indian ridge(SWIR) on the Chinese DY125-34 cruise had not been re-synchronized from GPS after recovery. So we attempted to estimate clock drift between each station pairs using time symmetry analysis(TSA) based on ambient noise cross-correlation. We tested the feasibility of the TSA method by analyzing daily noise cross-correlation functions(NCFs) that extract from the data of another OBS experiment on the Chinese DY125-40 cruise with known clock drift and the same deployment site. The results suggest that the NCFs' travel time of surface wave between any two stations are symmetrical and have an opposite growing direction with the date. The influence of different band-pass filters,different components and different normalized methods was discussed. The TSA method appeared to be optimal for the hydrophone data within the period band of 2–5 s in dozens of km-scale interstation distances. A significant clock drift of ~2 s was estimated between OBSs sets through linear regression during a 108-d deployment on the Chinese cruise DY125-34. Time correction of the OBS by the ambient noise cross-correlation was demonstrated as a practical approach with the appropriate parameters in case of no GPS re-synchronization. Seismic monitoring using ocean bottom seismometers(OBS) is an efficient method for investigating earthquakes in mid-ocean ridge far away from land. Clock synchronization among the OBSs is difficult without direct communication because electromagnetic signals cannot propagate efficiently in water. Time correction can be estimated through global positioning system(GPS) synchronization if clock drift is linear before and after the deployment. However, some OBSs in the experiments at the southwest Indian ridge(SWIR) on the Chinese DY125-34 cruise had not been re-synchronized from GPS after recovery. So we attempted to estimate clock drift between each station pairs using time symmetry analysis(TSA) based on ambient noise cross-correlation. We tested the feasibility of the TSA method by analyzing daily noise cross-correlation functions(NCFs) that extract from the data of another OBS experiment on the Chinese DY125-40 cruise with known clock drift and the same deployment site. The results suggest that the NCFs' travel time of surface wave between any two stations are symmetrical and have an opposite growing direction with the date. The influence of different band-pass filters,different components and different normalized methods was discussed. The TSA method appeared to be optimal for the hydrophone data within the period band of 2–5 s in dozens of km-scale interstation distances. A significant clock drift of ~2 s was estimated between OBSs sets through linear regression during a 108-d deployment on the Chinese cruise DY125-34. Time correction of the OBS by the ambient noise cross-correlation was demonstrated as a practical approach with the appropriate parameters in case of no GPS re-synchronization.
出处 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2018年第5期39-46,共8页 海洋学报(英文版)
基金 China Ocean Mineral Resources R&D Association Major Project under contract No.DY135-S1-01 the National Natural Science Foundation of China under contract Nos 41506078,41706042 and 41522404 the Basic Research Foundation of Second Institute of Oceanography,SOA under contract No.JG0608
关键词 clock drift cross-correlation ambient noise OBS clock drift cross-correlation ambient noise OBS
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