基于GEOSS的地震遥感热异常时空分析方法与检验
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摘要
从海量对地观测数据中有效识别出构造活动异常信息并揭示其时空演变特征是地震防灾减灾的重大需求。本论文针对地震遥感热异常识别中亟需解决的关键问题,顾及地球系统多圈层耦合效应,利用地表温度、近地表气温、热红外亮温、温度日较差、长波辐射、地表潜热通量等多个热参数及卫星云图、电离层参数,开展了基于全球综合地球观测系统(GEOSS)的地震遥感热异常分析方法研究,并进行了应用验证。研究提出了地震遥感热异常分析的LCA耦合模式,并基于GEOSS建立了兼顾偏量-时间-空间关系的热异常分析方法(DTS-T);提出了基于NCEP-FNL数据的地震遥感热异常逐像元分析方法,检验了MERRA数据的适用性与优势；此外,还辨析了红外亮温与线性云异常的关系,探索了地表潜热通量与电离层异常在中国西部地震前的准同步性。
The critical issues in the research and practice of earthquake disaster prevention and reduction are how to recognize the anomaly information related to tectonic activity from massive Earth observations, and how to reveal it's qualitative and quantitative evolution features in time and space. In consideration of the coupling effect among multiple Earth's spheres, this thesis has studied seismicity thermal anomaly with worldwide typical earthquakes being examples, using multiple parameters provided by the developing Global Earth Observing System of Systems (GEOSS), including surface temperature, air temperature, thermal infrared brightness temperature, daily temperature range (DTR), outgoing long-wave radiations (OLR), and surface latent heat flux (SLHF), as well as satellite cloud map and ionosphere parameters. A lithosphere-coversphere-atmosphere (LCA) coupling model is suggested and a deviation-time-space-thermal (DTS-T) method for GEOSS-based seismicity anomaly recognition is proposed; a NCEP-FNL-based per-pixel method is proposed and a new data source MERRA with better solutions in space and time is introduced; Furthermore, the relation between TIR anomaly and earthquake cloud is demonstrated, the synchronous of SLHF and ionosphere anomalies before earthquakes are analyzed.
The critical issues in the research and practice of earthquake disaster prevention and reduction are how to recognize the anomaly information related to tectonic activity from massive Earth observations, and how to reveal it's qualitative and quantitative evolution features in time and space. In consideration of the coupling effect among multiple Earth's spheres, this thesis has studied seismicity thermal anomaly with worldwide typical earthquakes being examples, using multiple parameters provided by the developing Global Earth Observing System of Systems (GEOSS), including surface temperature, air temperature, thermal infrared brightness temperature, daily temperature range (DTR), outgoing long-wave radiations (OLR), and surface latent heat flux (SLHF), as well as satellite cloud map and ionosphere parameters. A lithosphere-coversphere-atmosphere (LCA) coupling model is suggested and a deviation-time-space-thermal (DTS-T) method for GEOSS-based seismicity anomaly recognition is proposed; a NCEP-FNL-based per-pixel method is proposed and a new data source MERRA with better solutions in space and time is introduced; Furthermore, the relation between TIR anomaly and earthquake cloud is demonstrated, the synchronous of SLHF and ionosphere anomalies before earthquakes are analyzed.
引文
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