区域地电观测网地电场日变化模型研究

应用泰勒多项式和曲面样条函数法建立了我国地电场观测台网中华东、 华北两个区域台网的地电场日变化(K_p≤5)模型，并对拟合结果进行了对比分析. 结果表明: ① 尽管地电场变化复杂，但用这两种方法建立的日变化模型相当吻合，模型曲线随时间的变化符合样本曲线随时间的变化; ② 用模型曲线可以描述其它年份同农历日期、 同等磁情时实测的地电场日变化; ③ 用模型曲线描述实测地电场日变化时，低磁情时得出的结果要优于高磁情时的结果; ④ 用多日样本曲线得到的模型曲线更能清晰地展示出地电场日变化的两次起伏波形、 幅度以及极值集中在午前午后等变化特点. 今后建立全国各区域台网不同磁情、 不同农历日期的地电场日变化模型可定量评价区域台网的地电场观测资料的质量，同时根据该模型能够分离出地电场的非正常变化，进而研判真实的异常，以服务于地震等灾害事件的预测以及地球电磁环境变化的监测等方面. 

DaiIy variation modeI of the geo-eIectric fieId based on the geo-eIectric data from the regionaI geo-eIectric observation networks

The planar and time-varying models (geomagnetic index K_p≤5) of the daily variation of the geo-electric field in two regional geo-electric networks in East China and North China are built up based on the Taylor polynomial and surface spline function methods, respectively. Then the fitting results are compared and analyzed. The results show that although the geo-electric field variation is more complex, the models of the daily variation fitted by the two methods are identical to each other, and the two model curves are consistent with the measured sample curves with the variation of time. The two model curves could be used to describe the measured daily variation on the same lunar date in other years with the similar geomagnetic index K_p. The daily variation results based on the two models on the condition of a low geomagnetic index are better than that on a high geomagnetic index. The average model curves based on multi-day sample curves more clearly show the daily variation features of geo-electric field such as the twice fluctuation waveform in some day and its amplitude and the extreme value concentrating on before and after noon. It is important to establish the daily variation models of geo-electric field for the different lunar date in the different geomagnetic indices in each regional network. The models can be used to quantitatively evaluate the quality of observation data of regional geo-electric field networks, and the geo-electric field anomaly measured by the networks can be picked up based on these models, which can be applied to prediction of disasters like earthquakes and monitoring the changes in the electromagnetic environment.