Classification of solar wind structures and intense geomagnetic storm alarms with self-organizing maps

Intense geomagnetic storms (D_st < −100 nT) usually occur when a large interplanetary duskward-electric field (with Ey > 5 mV m⁻¹) lasts for more than 3 h. In this article, a self-organizing map (SOM) neural network is used to recognize different patterns in the temporal variation of hourly averaged Ey data and to predict intense storms. The input parameters of SOM are the hourly averaged Ey data over 3 h. The output layer of the SOM has a total of 400 neurons. The hourly Ey data are calculated from solar wind data, which are provided by NSSDC OMNIWeb and ACE spacecraft and contain information on 143 intense storms and a fair number of moderate storms, weak storms and quiet periods between September 3, 1966 and June 30, 2002. Our results show that SOM is able to classify solar wind structures and therefore to give timely intense storm alarms. In our SOM, 21 neurons out of 400 are identified to be closely associated with the intense storms and they successfully predict 134 intense storms out of the 143 ones selected. In particular, there are 14 neurons for which, if one or more of them are present, the occurrence probability of intense storms is about 90%. In addition, several of these 14 neurons can predict big magnetic storm (D_st  −180 nT). In summary, our method achieves high accuracy in predicting intense geomagnetic storms and could be applied in space environment prediction.     

On the correlation of the solar wind observed at the L5 point and at the Earth

The L5 point is a promising location for forecasting co-rotating high-speed streams in the solar wind arriving at the Earth. We correlated the solar wind data obtained by the Nozomi spacecraft in interplanetary space and by the Advanced Composition Explorer (ACE) at the L1 point, and found that the correlation is significantly improved from that of the 27-day recurrence of ACE data. Based on the correlation between the two spacecraft observations, we estimated the correlation of the solar wind velocity between the L5 point and at the Earth, and found that the correlation coefficient was about 0.78 in late 1999, while that of the 27-day recurrence was 0.51. Eighty-eight percent of the velocity difference falls within 100 km/s between the L5 point and the Earth. This demonstrates the potential capability of solar wind monitoring at the L5 point to forecast the geomagnetic disturbances 4.5 days in advance.     

我国多跑道运行下的航空气象服务

本文从跑道必须配置的自动气象观测系统(AWOS)入手,主要从四个方面对多跑道(两条或以上)运行下的航空气象服务进行了探讨。一是主要与航空气象人员对外服务有关,如本场天气报告(METAR、SPECI)中数据采集基准点的选择、跑道视程的显示、修正海平面气压采集等的归纳;二是管制部门、机场等用户所需要的相关气象数据信息显示方式、更新速率及如何理解等;三是探讨如何为多跑道运行提供精细化、临近的预报技术支持;最后,本文对航站自动情报服务系统(ATIS)中气象报告种类的选取及注意事项进行了探讨,指出该系统目前存在的问题和需要改进的地方。     

模型自由飞试验——研究航天飞机天气侵蚀问题的必要途径

本文阐明了研究航天飞机天气侵蚀效应的必要性,分析了天气侵蚀试验的模拟条件,论述了模型自由飞模拟试验在航天飞机和其它再入飞行器的天气侵蚀问题研究中的作用,最后对我国开展航天飞机天气侵蚀研究之技术途径提出了一些看法。     

Effects of space weather on the ionosphere and LEO satellites’ orbital trajectory in equatorial,low and middle latitude

We study the effects of space weather on the ionosphere and low Earth orbit (LEO) satellites’ orbital trajectory in equatorial, low- and mid-latitude (EQL, LLT and MLT) regions during (and around) the notable storms of October/November, 2003. We briefly review space weather effects on the thermosphere and ionosphere to demonstrate that such effects are also latitude-dependent and well established. Following the review we simulate the trend in variation of satellite’s orbital radius (r), mean height (h) and orbit decay rate (ODR) during 15 October–14 November 2003 in EQL, LLT and MLT. Nominal atmospheric drag on LEO satellite is usually enhanced by space weather or solar-induced variations in thermospheric temperature and density profile. To separate nominal orbit decay from solar-induced accelerated orbit decay, we compute $r\text{,}h$ and ODR in three regimes viz. (i) excluding solar indices (or effect), where $r=r_0\text{,}h=h_0$ and $\mathit{ODR}={\mathit{ODR}}_0$ (ii) with mean value of solar indices for the interval, where $r=r_m\text{,}h=h_m$ and $\mathit{ODR}={\mathit{ODR}}_m$ and (iii) with actual daily values of solar indices for the interval ($r\text{,}h$ and ODR). For a typical LEO satellite at h?=?450?km, we show that the total decay in r during the period is about 4.20?km, 3.90?km and 3.20?km in EQL, LLT and MLT respectively; the respective nominal decay ($r_0$) is 0.40?km, 0.34?km and 0.22?km, while solar-induced orbital decay ($r_m$) is about 3.80?km, 3.55?km and 2.95?km. h also varied in like manner. The respective nominal ${\mathit{ODR}}_0$ is about 13.5?m/day, 11.2?m/day and 7.2?m/day, while solar-induced ${\mathit{ODR}}_m$ is about 124.3?m/day, 116.9?m/day and 97.3?m/day. We also show that severe geomagnetic storms can increase ODR by up to 117% (from daily mean value). However, the extent of space weather effects on LEO Satellite’s trajectory significantly depends on the ballistic co-efficient and orbit of the satellite, and phase of solar cycles, intensity and duration of driving (or influencing) solar event.     

An empirical model to predict the 1-AU arrival of interplanetary shocks

We extend the empirical coronal mass ejection (CME) arrival model of Gopalswamy et al. [Gopalswamy, N. et al. Predicting the 1-AU arrival times of coronal mass ejections, J. Geophys. Res. 106, 29207, 2001] to predict the 1-AU arrival of interplanetary (IP) shocks. A set of 29 IP shocks and the associated magnetic clouds observed by the Wind spacecraft are used for this study. The primary input to this empirical shock arrival model is the initial speed of white-light CMEs obtained using coronagraphs. We use the gas dynamic piston–shock relationship to derive the ESA model which provides a simple means of obtaining the 1-AU speed and arrival times of interplanetary shocks using CME speeds.     

On one approach to space weather studies from ground based observations during 1953–2001

The cross correlation of daily values of coronal hole areas at the eastern limb of the Sun constructed from the ground based measurements of the green coronal line and daily mean cosmic ray intensities over long time periods shows asymmetry: at the maximum of their 27 day cycle, cosmic ray intensities are better correlated with coronal hole areas 66 days before than with the current value. This indicates the potential for using coronal emission data as one of the parameters for eventual prediction of the level of cosmic ray flux at neutron monitor energies.     

汽车密封条可重构生产线全生命周期评估

概述了LCA(L ife cycle assessm en t,全生命周期评价)基本内容,结合汽车车窗密封条可重构生产线的研究,给出了其系统边界、模型和设定。针对可重构生产线生命周期各个阶段,分析图表显示产生选定环境影响物质的数量,包括CO2、有害物质和能源消耗。LCA分析软件E co-IT计算结果显示,该密封条生产线的环境影响指数有11×103Pt来源于系统的使用阶段。超过5×103Pt的影响指数来源于加工或重建一个新系统,而通过重构系统只产生少于0.30×103Pt影响指数。本文旨在采用一个科学方法来评价可重构制造系统生命周期的能源消耗和环境影响因素,并给出可重构制造系统有益于可持续发展这一结论。     

Helio-geomagnetic influence in cardiological cases

The effects of the energetic phenomena of the Sun, flares and coronal mass ejections (CMEs) on the Earth’s ionosphere–magnetosphere, through the solar wind, are the sources of the geomagnetic disturbances and storms collectively known as Space Weather. The research on the influence of Space Weather on biological and physiological systems is open. In this work we study the Space Weather   impact on Acute Coronary Syndromes (ACS) distinguishing between ST-segment elevation acute coronary syndromes (STE–ACS) and non-ST-segment elevation acute coronary syndromes (NSTE–ACS) cases. We compare detailed patient records from the 2nd Cardiologic Department of the General Hospital of Nicaea (Piraeus, Greece) with characteristics of geomagnetic storms (_DST${\mathrm{D}}_{\mathit{ST}}$), solar wind speed and statistics of flares and CMEs which cover the entire solar cycle 23 (1997–2007). Our results indicate a relationship of ACS to helio-geomagnetic activity as the maximum of the ACS cases follows closely the maximum of the solar cycle. Furthermore, within very active periods, the ratio NSTE–ACS to STE–ACS, which is almost constant during periods of low to medium activity, changes favouring the NSTE–ACS. Most of the ACS cases exhibit a high degree of association with the recovery phase of the geomagnetic storms; a smaller, yet significant, part was found associated with periods of fast solar wind without a storm.     

Influence of ionospheric perturbations in GPS time and frequency transfer

The stability of GPS time and frequency transfer is limited by the fact that GPS signals travel through the ionosphere. In high precision geodetic time transfer (i.e. based on precise modeling of code and carrier phase GPS data), the so-called ionosphere-free combination of the code and carrier phase measurements made on the two frequencies is used to remove the first-order ionospheric effect. In this paper, we investigate the impact of residual second- and third-order ionospheric effects on geodetic time transfer solutions i.e. remote atomic clock comparisons based on GPS measurements, using the ATOMIUM software developed at the Royal Observatory of Belgium (ROB). The impact of third-order ionospheric effects was shown to be negligible, while for second-order effects, the tests performed on different time links and at different epochs show a small impact of the order of some picoseconds, on a quiet day, and up to more than 10 picoseconds in case of high ionospheric activity. The geomagnetic storm of the 30th October 2003 is used to illustrate how space weather products are relevant to understand perturbations in geodetic time and frequency transfer.