An Adaptive Network-based Fuzzy Inference System for the detection of thermal and TEC anomalies around the time of the Varzeghan,Iran, (Mw = 6.4) earthquake of 11 August 2012

Anomaly detection is extremely important for forecasting the date, location and magnitude of an impending earthquake. In this paper, an Adaptive Network-based Fuzzy Inference System (ANFIS) has been proposed to detect the thermal and Total Electron Content (TEC) anomalies around the time of the Varzeghan, Iran, (M_w = 6.4) earthquake jolted in 11 August 2012 NW Iran. ANFIS is the famous hybrid neuro-fuzzy network for modeling the non-linear complex systems. In this study, also the detected thermal and TEC anomalies using the proposed method are compared to the results dealing with the observed anomalies by applying the classical and intelligent methods including Interquartile, Auto-Regressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN) and Support Vector Machine (SVM) methods. The duration of the dataset which is comprised from Aqua-MODIS Land Surface Temperature (LST) night-time snapshot images and also Global Ionospheric Maps (GIM), is 62 days. It can be shown that, if the difference between the predicted value using the ANFIS method and the observed value, exceeds the pre-defined threshold value, then the observed precursor value in the absence of non seismic effective parameters could be regarded as precursory anomaly. For two precursors of LST and TEC, the ANFIS method shows very good agreement with the other implemented classical and intelligent methods and this indicates that ANFIS is capable of detecting earthquake anomalies. The applied methods detected anomalous occurrences 1 and 2 days before the earthquake. This paper indicates that the detection of the thermal and TEC anomalies derive their credibility from the overall efficiencies and potentialities of the five integrated methods.     

TEC variations analysis concerning Haiti (January 12, 2010) and Samoa (September 29, 2009) earthquakes

Two datasets of total electron content (TEC) time series have been analyzed in this study to locate relevant anomalous variations in recent major Haiti and Samoa Islands earthquakes prior to the events. The duration of two datasets is 45 and 65 days for Haiti and Samoa Islands earthquakes, respectively, each at a time resolution of 2 h.     

Variations in the ionospheric scale height parameter at the F2 peak over Grahamstown,South Africa

The Grahamstown, South Africa (33.3°S, 26.5°E) ionospheric field station operates a Lowell digital pulse ionospheric sounder (Digisonde) whose output includes scaled parameters derived from the measured ionogram. One of these output parameters is the ionospheric scale height parameter (H), and this paper presents an analysis of the seasonal, diurnal, and solar activity variations of this parameter over the Grahamstown station. Ionosonde data from three years 2002, 2003, and 2004 were used in this study. The data was subjected to a general trend analysis to remove any outliers and then the monthly median data were used to explore the different variations. The results of this analysis were found to be similar to what has already been presented in the literature for low latitude stations, and are presented as well as the correlation at this mid-latitude station between the H parameter, the IRI shape parameter (B0), and the peak electron density (NmF2).     

The topside sounder database – Data screening and systematic biases

The ionospheric topside sounder measurement database developed at the US National Space Science Data Center (NSSDC) is a valuable source of information when investigating the composition and complex dynamics of the upper ionosphere. The database is increasingly used by many scientists around the world for both research and development of empirical models. However, there is always a danger of indiscriminately using the data without properly assessing the data quality and applicability for a given purpose. This paper is concerned with the issue of data screening and pre-processing of the Alouette/ISIS topside sounder database. An overview of the original database availability and formatting is given and the use of solar and geomagnetic indices is discussed. Data screening procedures, concerning detection and handling of erroneous profiles, are also presented. Special attention is drawn to the systematic biases observed in the database and the possibilities for their removal.     

我国中部地区电离层扰动时空尺度的统计分析

将最大熵动态互普方法用于高频多普勒台阵数据处理，从覆盖太阳活动高、低年份的高频多普勒台阵观测数据中，得出了中国中部地区电离层声重波扰动的传播方向、时空尺度等参量之间的统计分布特性，进而探讨了有关扰动源的情况，结果表明，极区源和局地源两种不同的激发源所激发的声波，分别反映了电离层扰动的全球传播和地区特性两种不同的特征。     

利用F区电离层特性参量获取等效中性风的方法及讨论

讨论利用电离层特性参量获取F层峰值高度附近中性风信息的三类方法.这些方法主要有:传统的和改进的伺服理论方法、借助电离层模式和数据同化思想的方法和刘立波等提出的方法.并以美国Millstone Hill非相干散射雷达浓度剖面和离子速度数据,以及澳大利亚Beveridge(37°S,144°E)FPI风场和测高仪数据为个例,初步考察利用电离层特性数据导出的等效中性风与观测值的一致性.     

Prediction tests by using “ISF” method for the geomagnetic disturbances

A so-called “ISF” prediction method for geomagnetic disturbances caused by solar wind storms blowing to the Earth is suggested. The method is based on a combined approach of solar activity, interplanetary scintillation (I) and geomagnetic disturbance observations during the period 1966–1982 together with the dynamics of solar wind storm propagation (S) and fuzzy mathematics (F). It has been used for prediction tests for 37 geomagnetic disturbance events during the descending solar activity phase 1984–1985, and was presented in 33rd COSPAR conference. Here, it has been improved by consideration of the three dimensional propagation characteristics of each event, the search for the best radio source and the influence of the southward components of interplanetary magnetic fields on the geomagnetic disturbances. It is used for prediction tests for 24 larger geomagnetic disturbance events that produced space anomalies during the period 1980–1999. The main results are: (1) for the onset time of the geomagnetic disturbance, the relative error between the observation, T_obs, and the prediction, T_pred, ΔT_pred/T_obs  10% for 45.8% of all events, 30% for 78.3% and >30% for only 21.7%; (2) for the magnetic disturbance magnitude, the relative error between the observation, ∑K_p,obs, and the prediction, ∑K_p,pred, Δ∑K_p,pred/∑K_p,obs  10% for 41.6% of all events, 30% for 79% and 45% for 100%. This shows that the prediction method described here has encouraging prospects for improving predictions of large geomagnetic disturbances in space weather events.     

模式化分析F区电离层赤道异常槽

利用二维低纬电离层理论时变模式模拟低纬电离层演化，考察影响赤道异常槽位置的物理因素．计算结果显示赤道槽有明显的季节、地方时和经度变化．以１１０°Ｅ为例，北半球夏季期间赤道槽一般在磁倾赤道北侧，最北达３°-３．５°Ｎ，而在北半球冬季期间一般位于磁倾赤道南侧，最南可达４°－５°Ｓ．进一步分析发现，赤道槽季节变化中光化电离率季节改变的影响很小，主要由水平中性风季节变化贡献．计算以８３天为例，白天赤道槽在地理经度１００°Ｅ附近最南，２８５°Ｅ附近最北，与观测特征基本一致．主要是背景大气水平风场的经度差异导致赤道槽位置的经度变化，而非前人认为直接由磁偏角控制的．     

仿真转台周期性干扰抑制的研究

提出采用加速度反馈方案,在无需加大系统带宽的情况下提高系统的动态刚度,从而提高了系统对周期性干扰的抑制能力。仿真结果表明,与传统PID控制相比,采用加速度反馈确实能够较好地抑制系统中的周期性干扰。     

A realistic simulation framework to evaluate ionospheric tomography

Observation of the 3-dimensional (3-D) electron density of the ionosphere is useful to study large-scale physical processes in space weather events. Ionospheric data assimilation and ionospheric tomography are methods that can create an image of the 3-D electron density distribution. While multiple techniques have been developed over the past 30 years, there are relatively few studies that show the accuracy of the algorithms. This paper outlines a novel simulation approach to test the quality of an ionospheric tomographic inversion. The approach uses observations from incoherent scatter radar (ISR) scans and extrapolates them spatially to create a realistic ionospheric representation. A set of total electron content (TEC) measurements can then be simulated using real geometries from satellites and ground receivers. This data set, for which the ‘truth’ ionosphere is known, is used as input for a tomographic inversion algorithm to estimate the spatial distribution of electron density. The reconstructed ionospheric maps are compared with the truth ionosphere to calculate the difference between the images and the truth.To demonstrate the effectiveness of this simulation framework, an inversion algorithm called MIDAS (Multi-Instrument Data Analysis Software) is evaluated for three geographic regions with differing receiver networks. The results show the importance of the distribution and density of GPS receivers and the use of a realistic prior conditioning of the vertical electron density profile. This paper demonstrates that when these requirements are met, MIDAS can reliably estimate the ionospheric electron density. When the region under study is well covered by GPS receivers, as in mainland Europe or North America, the errors in vertical total electron content (vTEC) are smaller than 1 TECu (2–4%) . In regions with fewer and more sparsely distributed receivers, the errors can be as high as 20–40%. This is caused by poor data coverage and poor spatial resolution of the reconstruction, which has an important effect on the calibration process of the algorithm.