Records of the tsunami induced by the 2010 Chilean earthquake from Xiaoqushan seafloor observatory in the East China Sea  

作　　者：ZHANG YanWei FAN DaiDu XU HuiPing 

机构地区：[1]State Key Laboratory of Marine Geology, Tongji University, Shanghai 200092, China

出　　处：《Chinese Science Bulletin》2011年第27期2957-2965,共9页

基　　金：supported by Shanghai Committee of Science and Technology (06DZ12012);State Key Lab of Marine Geology (MG200907 and MG200910);Shanghai Municipal Natural Science Foundation (11ZR1438800);the Program for Young Excellent Talents in Tongji University (2009KJ045)

摘　　要：Sea-level variation can be induced by periodic tides, stochastic wind, air pressure, and swell. Larger sea-level variation has the potential to cause coastal disasters. In this paper, real-time continuous data obtained by the Xiaoqushan seafloor observatory in the East China Sea were analyzed employing frequency power spectral and tidal harmonic methods to extract the major components and periodicities of sea-level change. The sea-level anomaly (sla) was calculated by subtracting the tidal components from the observed sea level data. In the study period, the correlation between sla and the local north-south wind speed was high with a correlation coefficient of 0.65 at the 95% confidence level. The local wind-induced sea-level anomaly (sla wind ) was therefore computed through linear fitting. Although sla wind is one of the main components of sla, the residual sea-level anomaly (sla residual ) obtained by subtracting sla wind from sla is not zero, suggesting that there are other factors besides wind. Detailed analysis of the sea-level data at the time of the 8.8-magnitude Chilean earthquake on February 27, 2010 showed a peak sla residual value of 0.48 m at around 15:00 on February 28, which was highly coincident with the tsunami arrival time forecast by the Pacific Tsunami Warning Center. The peak sla residual event is therefore linked with the tsunami induced by the 2010 Chilean earthquake. This is the first time that a tsunami has been detected using real-time continuous data recorded by a seafloor observatory in the sea off China. Such observations are expected to improve tsunami forecast models and promote the development of a tsunami warning system and a seafloor observatory network in the East China Sea.Sea-level variation can be induced by periodic tides, stochastic wind, air pressure, and swell. Larger sea-level variation has the potential to cause coastal disasters. In this paper, real-time continuous data obtained by the Xiaoqushan seafloor observatory in the East China Sea were analyzed employing frequency power spectral and tidal harmonic methods to extract the major components and periodicities of sea-level change. The sea-level anomaly （sla） was calculated by subtracting the tidal components from the observed sea level data. In the study period, the correlation between sla and the local north-south wind speed was high with a correlation coefficient of 0.65 at the 95% confidence level. The local wind-induced sea-level anomaly （sla wind ） was therefore computed through linear fitting. Although sla wind is one of the main components of sla, the residual sea-level anomaly （sla residual ） obtained by subtracting sla wind from sla is not zero, suggesting that there are other factors besides wind. Detailed analysis of the sea-level data at the time of the 8.8-magnitude Chilean earthquake on February 27, 2010 showed a peak sla residual value of 0.48 m at around 15：00 on February 28, which was highly coincident with the tsunami arrival time forecast by the Pacific Tsunami Warning Center. The peak sla residual event is therefore linked with the tsunami induced by the 2010 Chilean earthquake. This is the first time that a tsunami has been detected using real-time continuous data recorded by a seafloor observatory in the sea off China. Such observations are expected to improve tsunami forecast models and promote the development of a tsunami warning system and a seafloor observatory network in the East China Sea.

关 键 词：海啸预警系统 海底观测站 中国东海 天文台 地震 智利 海平面变化 SLA 

分 类 号：P715[天文地球—海洋科学]