基金项目:中国地震局地震预测重点实验室专项(0210240202,30214240122,40414600103)和中国地震局地震预测研究所基本科研业务费项目“首都圈地震重点监视区活动断裂带气体地球化学流动测量和地震应急”(02122408)联合资助.
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利用印度尼西亚Bukit Koto Tabang(BKT)观测站的地面和大气红外探测仪(AIRS)卫星观测数据,分别提取了该观测站2004年和2005年苏门答腊两次M>8.0地震前后地面和卫星观测所获得的CO总量、近地面(1 000 hPa)CO体积分数和O3总量的高光谱气体地球化学信息,对BKT台站附近卫星观测数据和地面观测数据进行了相互验证。结果 表明两次大地震前卫星和地面观测均捕获到了CO和O3异常,其中卫星观测获得的CO总量和CO体积分数与地面测得的CO浓度呈强正相关,相关系数分别为0.83和0.75,表明CO浓度异常可能主要源于孕震过程中地下逸出的气体,大气中的化学反应对CO异常的贡献次之。O3卫星观测结果与地面观测结果也呈正相关关系(r=0.49),地震前O3异常可能主要归因于地震前地下逸出的气体在大气中的化学反应。地面观测的CO和O3浓度在两次地震前标准偏差变大,且CO和O3浓度变化与分别以地面观测站和地震震中为中心从卫星数据提取的气体浓度与地面观测数据变化趋势一致。研究结果丰富了利用高光谱卫星数据提取地震前后气体地球化学异常信息的方法。
Using the ground-based observation data recorded by Bukit Koto Tabang(BKT)observational station in Indonesian and observation satellite data by atmospheric infrared sounder(AIRS),the hyperspectral gas geochemical information of CO total column,CO volume mixing ratio at 1000 hPa and O3 total column from ground-based and satellite data before and after two Sumatra M>8.0 earthquakes were abstracted,and the ground-based and satellite data of BKT observational station were validated. The results show that the anomalies of CO and O3 were both found before two Sumatra M>8.0 earthquakes from ground-based and satellite data. Both CO total column and volume fraction at 1000 hPa from satellite data had significantly positive correlation with CO concentration from the ground-based data,and the correlation coefficient were 0.83 and 0.75 respectively,which indicated that the CO concentration anomalies was mainly attributed to degassing from the solid earth in the pregnant process and the secondary reason was chemical reactions in the atmosphere. The O3 total column from AIRS data and O3 concentration from ground-based data showed positive correlation with correlation coefficient 0.49,indicating the anomalies of O3 mainly caused by chemical reactions of the degassed gases in the atmosphere. The standard deviations of CO and O3 concentrations from ground-based data increased before two earthquakes,which was almost consistence with gas concentration abstracted from satellite data by taking the BKT station and epicenter as centre respectively and variation trends of ground-based observation data. The results widened the approach of extracting gaseous geochemistry information from hyperspectral satellite data especially.