全球雷电活动分布和强度的探测与量化方法研究

Research on the Global Lightning Activity(GLA) is in persistent demands by multiple disciplines, which require lightning information in the global scale, for instance implementing the Global Energy Interconnection(GEI), analyzing the Global Electrical Circuit(GEC), and investigating the Global Temperature Changes(GTC). The existed GLA detection methods have the boundedness in the global lightning detection efficiency since the time sampling resolution is too low in the satellite-based observation and the detection region measured by multiple VLF(very low frequency) stations can not entirely cover the Earth for the limitation in station installments and maintains. The efficient detection and quantification methodology are still pending in monitoring the distribution and intensity of GLA. Therefore, a global lightning activity inversion algorithm(GLA-IA) based on analyzing the Schumann Resonances and electromagnetic propagation characteristics is put forward to deduce the distribution and intensity of lightning in the globe, which only needs the continuous ELF(extremely low frequency) signals measured from a few or even one station. The evaluation method for qualifying the ELF signals will be firstly established in the research. For timely transferring the ELF data from the worldwide multiple ELF stations, we will develop the low-power automatic transmission and real-time synchronization processing technology to supply ELF data to GLA-IA. The GLA will be obtained by GLA-IA to offer the fundamental lightning data for the GEI, GEC, and GTC research. The role of GLA serving as a thermometer of GTC is further discussed by the GLA data deduced from the research in order to enhance the resolution and accuracy of GTC.

在全球能源互联网战略、全球电路分析、全球温度变化研究等对广域雷电信息数据的强烈需求下，全球雷电活动研究成为当前较为关注的问题。已有全球雷电活动监测方法存在空基观测采样周期长、甚低频系统布站数量和条件受限制、雷电探测效率不高等问题，如何高效地探测和量化全球雷电活动成为研究的重点与难点。为此，研究提出基于舒曼共振和电磁传播特性分析的全球雷电激励源反演算法，通过极少数（小于9个）极低频（ELF）监测站实现全球雷电活动分布和强度的探测与量化，提高全球雷电活动的探测效率。通过研究，提出用于多站ELF信号数据的质量评价分析方法和低功耗自动传输与实时同步处理技术，建立基于多站ELF信号数据的全球雷电激励源反演方法，量化全球雷电活动的位置和强度，为全球电路分析提供基础；研究全球雷电活动对全球温度变化的敏感增益放大关系，提高全球温度变化的监测精度和灵敏度。

雷电可为人类生活和工业生产带来严重的事故，雷电活动实时监测技术可以测量落雷位置和相应的雷电参数，为雷电事故定位、分析和雷电防护研究提供及时有效的雷电信息。全球雷电活动及其实时监测方法是国际前沿和难点研究，国外雷电研究学者已投入大量精力开展探索，国内专家学者也指出我国应重视并开展此方面的研究。为此，本项目基于舒曼共振分析和电磁传播反演的思路，研究基于少数极低频ELF电磁信号站的全球雷电激励源反演方法，依据全球32个ELF监测站的电磁数据，建立电磁数据整合和信号幅频校准算法，基于FFT变换和洛伦兹拟合处理，提出了多站ELF信号数据的质量评价分析方法，建立了低功耗自动传输与实时同步处理技术。提取得到用于雷电活动反演的相关数据，建立了应用ELF信号数据的基于舒曼共振和电磁传播特性分析的全球雷电激励源反演算法。其中，针对现有舒曼共振信号分析方法得到的有效状态参量较少和多维矩阵方程建立与求解存在的问题，研究改进了舒曼共振信号关键参数和状态参量的分析方法，建立了基于最佳前向传播模型的敏感多维矩阵方程组，创新性地将多维多源多频反演问题归一至线性反演求解空间，通过线性反演求解的唯一性得到多维多源多频散点激励源反问题的收敛解和唯一解。本项目可为我国建立全球雷电监测系统提供算法基础。