Systematic examination of the geomagnetic storm sudden commencement using multi resolution analysis

Geomagnetic storm sudden commencements (SSC) contain a wealth of information which is useful in many applications. It is important to point out that the SSCs used in this study are sampled at the rate of one sample per second in order get use of such high resolution data. In this paper, two studies are made on the geomagnetic SSC and an SSC onset automatic detection algorithm is introduced. The first study is about finding the relationship between the SSC rise time and its amplitude. Where it is found that there is a positive correlation between the amplitude and the amplitude gradient which is the amplitude divided by rise time. The second study is checking the spectrum of the SSC, starting from its onset until the end of the SSC rise time. This check had proved that the SSC contains both low and high frequency regions. This led us to introduce a new term, namely the SSC variation rate (VR). This VR is defined as the maximum rate of change of the field in the higher-frequency region of the SSC. These two studies were the guide to build an SSC automatic detector of one sample per second data using multi resolution analysis (MRA) of the discrete wavelet transform (DWT). The data set contains 134 SSCs with different VRs that were collected from the Circum-pan Pacific Magnetometer Network (CPMN). It is found that the standard deviation of the detection error is 41 s and that the average error is 9 s. From the calculated error distribution function, it is found that the detection error is within the range of −1.5 to 3 min. The detection process, as will be shown in the article, takes 70 s for one station and 3 min if the decision is related to the detection(s) of other stations. These results demonstrate the superiority of the proposed algorithm over other algorithms in which the detection error ranges between −8 and 5 min and the detection process takes 2–10 min. In addition to being faster and more accurate than the other algorithms, the proposed algorithm is the first algorithm that automatically detects the SSC onset times from high-resolution data unlike previous studies that focused on determining the SSC times automatically using one-minute resolution data.     

磁暴对海南地区电离层扩展F的影响

利用2002年2月至2007年12月海南地区DPS-4测高仪观测数据, 用统计分析方法研究了磁暴对电离层扩展F的影响. 结果认为磁暴从整体上抑制了扩展F现象的发生. 但若把扩展F分为不同类型, 则结果却有所不同. 对于频率型(FSF), 在2002年和2003年磁暴对其有促发作用, 在2004---2007年有抑制作用; 对于区域型(RSF), 在2002---2005年磁暴对其有抑制作用, 在2006年和2007年, 对其有弱促发作用; 对于混合型(MSF), 在2002年磁暴对其有抑制作用, 在2003年和2004年有促发作用, 从2005年开始, 磁暴对其有抑制作用; 对于强区域型 (SSF), 在2002---2004年磁暴对其有抑制作用, 在2005年和2006年有促发作用, 2007年有弱抑制作用.      

不同强度磁暴期间热层大气密度响应特征分析

利用CHAMP卫星数据,对2002-2008年12个不同强度磁暴事件期间的热层大气密度变化特征进行分析,并研究对应磁暴期间大气模式NRLMSISE-00分布特征.结果表明,大磁暴期间日侧大气密度峰值从高纬到低纬的时间延迟为2h,中小磁暴期间的延迟时间为3～4h;春秋季暴时大气密度分布基本呈南北对称分布,而夏冬季大气密度的分布是夏半球大于冬半球,春秋季暴时大气密度大于夏冬季;NRLMSISE-00大气模式得到的热层大气密度很好的体现了半球分布以及季节分布的特征,但模式模拟结果偏小;Dst指数峰值比ap指数峰值更能反应大气密度的变化情况.      

Highlights about the performances of storm-time TEC modelling techniques for low/equatorial and mid-latitude locations

A statistical evaluation of storm-time total electron content (TEC) modelling techniques over various latitudes of the African sector and surrounding areas is presented. The source of observational TEC data used in this study is the Global Navigation Satellite Systems (GNSS), specifically the Global Positioning Systems (GPS) receiver networks. For each selected receiver station, three different storm-time models based on empirical orthogonal functions (EOF) analysis, non-linear regression analysis (NLRA) and Artificial neural networks (ANN), were implemented. Storm-time GPS TEC data used for both development and validation of the models was selected based on the storm criterion of $\mathit{Dst}?-50$ nT or $K_p?4$ to take into account both coronal mass ejections (CMEs) and co-rotating interaction regions (CIRs) driven storms, respectively. To make an independent test of the models, storm periods considered for validation were excluded from datasets used during the implementation of the models and results are compared with observations, monthly median values, and International Reference Ionosphere (IRI-2016) predictions. Considering GPS TEC as reference, a statistical analysis performed over six storm periods reserved for validation revealed that ANN model is about 10%, 26%, and 58% more accurate than EOF, NLRA, and IRI models, respectively. It was further found that, EOF model performs 15%, and 44% better than NLRA, and IRI models, respectively, while NLRA is 25% better than IRI. On the other hand, results are also discussed referring to the background ionosphere represented by monthly median TEC (MM TEC) and statistics are provided. Moreover, strengths and weaknesses of each model are highlighted.     

Study of maximum electron density NmF2 at Karachi and Islamabad during solar minimum (1996) and solar maximum (2000) and its comparison with IRI

The monthly hourly medians of maximum electron density, N_mF₂, at two Pakistani ionospheric stations, Karachi and Islamabad, have been determined for solar minimum (1996) and solar maximum (2000) and compared with IRI predictions using the URSI coefficients. At night and pre-noon period the N_mF₂ values at both stations are almost equal during the 2 years. However, at post-noon the values at Karachi are considerably larger than those at Islamabad due to the equatorial or geomagnetic anomaly. Karachi (geomag. coord. 16.44°N, 139.08°E) lies near the region of the equatorial anomaly (+20 and −20 geomagnetic latitude), so most of the N_mF₂ values at Karachi are larger than those at Islamabad (geomag. coord. 24.46°N, 145.67°E). The maximum monthly values of N_mF₂ show a semi-annual variation at Karachi and Islamabad both during 1996 and 2000 as predicted by IRI.     

The geomagnetic solar flare effect identified by SIIG as an indicator of a solar flare observed by GOES satellites

This paper studies the efficiency of geomagnetic solar flare effects (gsfe) in X solar flare detection; so during the period 1999–2007 a comparison between solar flare (sf) observed by satellites of the Geostationary Operational Environmental Satellite (GOES) programme and gsfe published by the Service International des Indices Geomagnetiques (SIIG) is made.     

液体火箭发动机推进剂泵诱导轮与离心轮的匹配

为获得诱导轮离心轮周向匹配的时序效应对离心泵外特性以及压力脉动的影响规律,阐释相关作用机制,采用基于分离涡仿真（DES）的离心泵三维全流道数值仿真方法,引入熵产理论以及压力脉动强度系数等先进分析方法对不同匹配角度下离心泵内能量损失机制及压力脉动特性进行了研究。结果表明：离心轮诱导轮的时序效应对泵外特性有一定的影响,随着匹配角度的增加,扬程和效率均呈现先减小后缓慢增大的趋势,扬程变化为0.8%,效率变化为1.2%,其影响机制由不同匹配角度下叶轮通道分离涡、叶轮叶片尾迹以及靠近隔舌处扩压器通道回流涡变化决定;时序效应对离心轮扩压器动静干涉效应影响显著,当诱导轮叶片尾缘位于离心轮相邻主叶片中间位置时,能够有效消除3倍频成分,显著降低泵内压力脉动水平,其中动静干涉区域以及隔舌处扩压器叶片表面压力脉动平均降幅分别达到14.5%和16.7%。     

宽频高幅值水力激振信号的产生与控制

为了研究火箭发动机全尺寸泵后供应系统的动力学特性,运用脉动压力发生器设计了一种宽频水力激振系统,开展了液流试验和数据分析。结果表明:水力激振系统可以在0~1200Hz的频率范围内,产生时域幅值超过1.5MPa、高信噪比的压力脉动信号,达到了宽频率范围、高激励幅值的目的。通过对电动机转速的控制实现激励频率的可控变化,以满足不同频率激励策略的要求。提高管路系统的入口稳态压力,可以提高激振信号的幅值。通过合适的局部流阻分布,可以在宽频范围内提高水力激振信号的幅值,提高信噪比。      

SABRE雷达及其观测的Pc5地磁脉动Ⅰ.统计分析结果

本文简要介绍了相干散射雷达SABRE及其观测Pc5地磁脉动的工作原理。1985—1989年观测数据的统计分析结果表明,相位向极传播脉动事件的出现率峰值在当地时间午夜附近,而向赤道传播事件的出现率峰值则在18:00LT左右。文中给出了上述两类脉动事件出现率的日变化,与地磁活动的相关,与背景电离层等离子体对流特性的关系等统计分析结果。     

广州地磁Z分量日变幅的谱特征

利用1972—1993年广州地磁资料，分析了Z分量日变幅的年平均、年变化和半年变化等低频成分的逐年变化，以及小于60天的短周期变化特征．同时对1972—1993年的F10.7日均值进行了谱分析．结果指出，广州地磁Z分量日变幅的年平均与太阳活动指数F10．7的年平均存在良好的线性相关；具有幅度大约5nT夏季极大的年变化，与太阳活动没有明显相关，是一种季节效应；存在春秋分极大的半年变化，幅度与太阳活动有关，高年的幅度明显大于低年；具有明显的与太阳自转相关的27天左右的变化和明显的与行星波有关的接近16日、10日、5日、2日等短周期变化．广州地磁Z分量日变幅的这些谱特征，有助于更深入地了解中低层大气对电离层影响的物理机制．