Detection and monitoring of earthquake precursors: TwinSat,a Russia–UK satellite project

There is now a body of evidence to indicate that coupling occurs between the lithosphere–atmosphere–ionosphere prior to earthquake events. Nevertheless the physics of these phenomena and the possibilities of their use as part of an earthquake early warning system remain poorly understood. Proposed here is a programme to create a much greater understanding in this area through the deployment of a dedicated space asset along with coordinated ground stations, modelling and the creation of a highly accessible database. The space element would comprise 2 co-orbiting spacecraft (TwinSat) involving a microsatellite and a nanosatellite, each including a suite of science instruments appropriate to this study. Over a mission duration of 3 years ∼ 400 earthquakes in the range 6–6.9 on the Richter scale would be ‘observed’. Such a programme is a prerequisite for an effective earthquake early warning system.     

A 2-d ionospheric model for low latitude area – Hong Kong

The ionosphere is an important part of the atmosphere and it is the largest error source of GNSS positioning for single-frequency users. So establishing a precise ionosphere model is one of the critical steps for satellite navigation and also for ionospheric research.     

Ionospheric reflection of the magnetic activity described by the index η

Differences in the external part of the vertical geomagnetic component point to the existence of local inhomogeneities in the magnetosphere or the ionosphere. Usually used magnetic indices are not sufficient to express the state of ionosphere, the common used global Kp index derived in the three-hour interval does not indicate much more rapidly changes appearing in ionosphere. Magnetic index η reflects ionospheric disturbances when other indices show very quiet conditions. Data of ionospheric characteristics (foE, foEs, h’E, h’F2) during 28-day long quiet day conditions (Kp = 0–2) in 2004 were analyzed. The correlations between strong local disturbances in ionosphere during very quiet days and high values of magnetic index η were found. The most sensitive to magnetic influence – ionospheric E layer data (foE characteristic) – reaches median deviations up to (+0.8 MHz and −0.8 MHz) during very low magnetic activity (Kp = 0–1). The high peaks (2–2.7) of the magnetic index η correlate in time with large local median deviations of foE. Such local deviations can suggest local inhomogeneities (vertical drifts) in the ionosphere. The correlation in space is not trivial. The strong peak of η is situated between the positive and negative deviations of foE. Additional observation is connected with correlation in time of the high η value with the negative median deviations of h’F2 (in some cases up to −90 km). The analysis was based on one-minute data recorded at each of 20 European Magnetic Observatories working in the INTERMAGNET network and from 19 ionosondes for 2004. Ionospheric data are sparse in time and in space in opposite to the magnetic data. The map of the magnetic indices can suggest the behavior of ionospheric characteristics in the areas where we have no data.     

Statistical modelling of radio wave propagation under sporadic E-Layer influence

A technique of modelling the one-hop radio wave propagation at middle latitudes in the presence of sporadic E-Layer is presented. The technique is focused on the performance of the long-term forecast of the maximum usable frequency range and on the increase of the radio communication reliability. Examples of calculation for medium-distance paths are shown.     

Towards a GPS-based TEC prediction model for Southern Africa with feed forward networks

In this paper, first results from a national Global Positioning System (GPS) based total electron content (TEC) prediction model over South Africa are presented. Data for 10 GPS receiver stations distributed through out the country were used to train a feed forward neural network (NN) over an interval of at most five years. In the NN training, validating and testing processes, five factors which are well known to influence TEC variability namely diurnal variation, seasonal variation, magnetic activity, solar activity and the geographic position of the GPS receivers were included in the NN model. The database consisted of 1-min data and therefore the NN model developed can be used to forecast TEC values 1 min in advance. Results from the NN national model (NM) were compared with hourly TEC values generated by the earlier developed NN single station models (SSMs) at Sutherland (32.38°S, 20.81°E) and Springbok (29.67°S, 17.88°E), to predict TEC variations over the Cape Town (33.95°S, 18.47°E) and Upington (28.41°S, 21.26°E) stations, respectively, during equinoxes and solstices. This revealed that, on average, the NM led to an improvement in TEC prediction accuracy compared to the SSMs for the considered testing periods.     

Ionospheric slab thickness – Analysis, modelling and monitoring

A review of the climatological and storm-time behaviour of the ionospheric slab thickness is presented based on long-time observations at a European mid-latitude site, Dourbes (50.1°N, 04.6°E), and on published results from other studies. An operational electron density and slab thickness monitoring system, established to provide real-time characterisation of the local ionospheric dynamics, is outlined together with some exemplary results.     

Storm time behavior of topside scale height inferred from the ionosphere–plasmasphere model driven by the F2 layer peak and GPS-TEC observations

The International Reference Ionosphere model extended to the plasmasphere, IRI-Plas, presents global electron density profiles and total electron content, TECiri, up to the altitude of the GPS satellites (20,000 km). The model code is modified by input of GPS-derived total electron content, TECgps, so that the topside scale height, Hsc, is obtained minimizing in one step the difference between TECiri and TECgps observation. The topside basis scale height, Hsc, presents the distance in km above the peak height at which the peak plasma density, NmF2, decays by a factor of e (∼2.718). The ionosonde derived F2 layer peak density and height and GPS-derived TECgps data are used with IRI-Plas code during the main phase of more than 100 space weather storms for a period of 1999–2006. Data of seven stations are used for the analysis, and data from five other stations served as testing database. It is found that the topside basis scale height is growing (depressing) when the peak electron density (critical frequency foF2) and electron content are decreased (increased) compared to the median value, and vice versa. Relative variability of the scale height, rHsc, and the instantaneous Hsc are inferred analytically in a function of the instantaneous foF2, median fmF2 and median Hmsc avoiding a reference to geomagnetic indices. Results of validation suggest reliability of proposed algorithm for implementation in an operational mode.     

A review of observed variability in the dayside ionosphere of Mars

Recent measurements by Mars Global Surveyor and Mars Express have greatly increased the number of observations of the martian dayside ionosphere available for study. Together with earlier measurements from the Viking era, these datasets have been used to investigate variations in well-known properties of the martian dayside ionosphere and to discover new ionospheric features. The dayside ionosphere includes the main peak, called the M2 layer, and a lower layer, called the M1 layer. In the topside, above the M2 layer, electron densities exponentially decrease with increasing altitude.     

低纬100—200km间电子数密度的变化

利用光化平衡模式计算了低纬100—200km间白天电子数密度的变化。求得E-F₁谷区的谷深,谷宽、谷高的变化特征。获得如下结果:a.太阳活动明显影响电子数密度随高度及太阳天顶角的变化,发现太阳活动指数与电子数密度间不仅存在正相关,而且存在负相关;b.太阳活动明显影响E-F₁谷区的形态。在一定太阳活动条件下,对同一太阳赤纬和地理纬度,谷深、谷宽与太阳天顶角的关系难以用一简单函数来表示;c.太阳耀斑、地磁活动对该区电子密度有明显影响;d.在讨论100—200km间电子密度时不能忽略O+（2P）和NO的光电离率。