An attempt is made to model the three-dimensional global structures and temporal variations of the ionospheric electron density (Ne) using the radio occultation (RO) Ne profile data obtained by the COSMIC/FORMOSAT-3, CHAMP and GRACE missions during the period from July 2006 to June 2017. The modeling technique we adopted is based on the empirical orthogonal function (EOF) analysis of the RO Ne dataset which is binned with grids of 2.5° in geomagnetic latitudes and 1/3 hr in geomagnetic local time (equivalent to 5° in geomagnetic longitudes) and 10 km in height. The EOF analysis decomposed the binned (gridded) Ne dataset into a series of eigen modes or basis functions (Ei) representing the variations with geomagnetic latitude, geomagnetic local time as well as height and the associated EOF amplitude coefficients (Ai) representing the variations with seasons as well as solar cycle activity. Our results showed that the EOF components (Ei, Ai) obtained by the EOF decomposition have different three-dimensional spatial structures with distinct features attributable to different factors or processes controlling the variations of the ionosphere: the first EOF component represents mainly the global mean structure of Ne and its temporal variation with seasons and solar cycle activity; the second EOF component represents mainly the seasonal control of the solar zenith angle on the ionosphere; the third EOF component is representative of the uplifting or lowering of the peak height where Ne reaches its maximum value; the fourth and fifth EOF components represent respectively the variations of the thickness of the ionosphere in the southern and northern hemispheres. It is found that the obtained eigen series converges quickly, with the first five EOF components contributing as high as 98% of the variances of the Ne dataset. We then modeled the EOF coefficients Ai obtained by the EOF decomposition using the harmonic functions representing the annual and semi-annual variations, with the solar cycle dependences being taken into account by including the changes of the harmonic amplitudes with the solar irradiance flux index F10.7. The Ne model is constructed using the Ai thus modeled and Ei obtained by the EOF decomposition. Comparison between the Ne model output results and the COSMIC-2 observational data showed that the modeled results capture well the global structures of the observational data and the model output results have very high linear correlation coefficients with the observational ones (R > 0.9), justifying the modeling technique used in our present study.

The platform dedicated to studies of extreme ultraviolet (EUV) laser on atom/molecule has been established recently at the Institute of Modern Physics, CAS, Lanzhou. The single ionization of helium with EUV photons of about 37.5 eV was conducted. Photoelectron angular distributions are obtained and compared with theoretical calculations from TDSE method.

We present our implementation of an automated very long baseline interferometry (VLBI) data-reduction pipeline that is dedicated to interferometric data imaging and analysis. The pipeline can handle massive VLBI data efficiently, which makes it an appropriate tool to investigate multi-epoch multiband VLBI data. Compared to traditional manual data reduction, our pipeline provides more objective results as less human interference is involved. The source extraction is carried out in the image plane, while deconvolution and model fitting are performed in both the image plane and the uv plane for parallel comparison. The output from the pipeline includes catalogues of cleaned images and reconstructed models, polarization maps, proper motion estimates, core light curves and multiband spectra. We have developed a regression strip algorithm to automatically detect linear or non-linear patterns in the jet component trajectories. This algorithm offers an objective method to match jet components at different epochs and to determine their proper motions.

The International Reference Ionosphere (IRI) is the most frequently used community empirical model. The latest version IRI2016 provides three options for the F2 peak height hmF2: AMTB2013, SHU-2015, and BSE-1979. In this paper, we used the hmF2 data derived by the ionosondes at Mohe, Beijing, Wuhan and Sanya ranging from year 2007 to 2016 to assess the performance of these three options in the model. The results show that the variability of the observed hmF2 versus local time, seasons and levels of solar activity could be reproduced well by the three options. However, the SHU-2015 option performs best at these four stations, followed by BSE-1979, and the AMTB2013 option is worst. Generally, the AMTB2013 and BSE-1979 options overestimate the hmF2 values, while the SHU-2015 option mainly underestimates the hmF2 values. This is the first evaluations of the three IRI2016 hmF2 options by manually scaled ionosonde data over China area to our knowledge. Overall, we recommend the usage of SHU-2015 hmF2 option over China region when using IRI2016 model in terms of hmF2 calculation. (C) 2017 COSPAR. Published by Elsevier Ltd. All rights reserved.

In this paper, variations of the topside ionospheric and plasmaspheric electron contents (TPEC) in the altitude range of ∼800 to 20,200 km are compared with the IRI_Plas model results for the low (2008) and high (2012) solar activity years using TEC data (podTEC) derived from the upward-looking precise orbit determination antenna on board COSMIC low Earth orbit (LEO) satellites tracking the GPS signals. For each year, the dataset were divided into groups according to four seasons: M-Equinox (March, April), J-Solstice (May June, July and August), S-Equinox (September, October) and D-Solstice (January, February, November, and December). Our study showed that the IRI_Plas model is able to reproduce reasonably well the main features of the observational TPEC’s latitudinal, diurnal as well as seasonal variation tendency when no longitudinal difference is taken into account. However, there exist discrepancies between the observational TPEC and the model results. Except for the daytime hours in the Equinoctial seasons of the high solar activity year 2012 when the IRI_Plas model results showed an overestimation, in general, the IRI_Plas model results underestimate the observational ones, in particular at nighttime hours in the low-latitude region. When the longitudinal difference is taken into account, the comparison study showed that the longitudinal dependence effect shown in the observational TPEC’s seasonal variations was not captured by the IRI_Plas model result. Moreover, the IRI_Plas model results tend to show a double-peak structure in the low-latitude region, a feature not appearing in the observational results.

We tried to study the variations of the plasmaspheric electron content(PEC)using the PEC data derived from the podTEC observation of the COSMIC low Earth orbit(LEO)satellite to the GPS satellite signals.We first give a brief introduce to the method we used to convert the slant podTEC to the vertical PEC.Then we used the converted PEC data of the year 2008 to study the variations of PEC with the geomagnetic latitude(MLAT),magnetic local time(MLT)and with four different seasons.Besides,we made a study on the longitudinal variation of PEC using the extracted PEC data from two different longitudes(120°E and 300°E).Our study showed that:(1)The distribution of PEC is mainly confined to a region within ±45°of the magnetic equator of the Earth;(2)PEC shows a well-defined diurnal variation pattern withhigher values during daytime hours than during nighttime hours.PEC reaches its peak value at the hour around 12—16MLT,whereas it reaches its minimum value at around 4—5MLT.(3)PEC has a lowest value in the June solstice season(May—August)compared with other seasons.(4)PEC shows an evident longitudinal variation and it has different seasonal variations for different longitudes.

In this paper, we present our recent work on developing an updated global model of the ionospheric F2 peak height hmF2 parameter by combining data from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC/FORMOSAT-3) radio occultation (RO) measurements and from the extended global ionosonde stations. In particular, 10 Chinese ionosonde stations' data are newly introduced into this study. The modeling technique used is based on a two-layer empirical orthogonal function (EOF) expansion. Global distributions of hmF2 maps calculated using the newly constructed global model and the one provided by the International Reference Ionosphere model (IRI-ITU-R) are compared with the global distributions of hmF2 obtained by the COSMIC RO measurements and quantitative statistical analysis of the differences between the model results and those of the COSMIC RO measurements is made for the low (2008) and high (2012) solar activity years. The obtained average root-mean-square differences (RMSEs) for our model are 27.7 km (11.1%) and 31.0 km (9.8%), respectively for the years 2008 and 2012, whereas those for the IRI-ITU-R model are 39.9 km (16.9%) and 35.0 km (11.6%), respectively. Comparison of the results calculated both by our model and the IRI-ITU-R model with the digisonde observation is also made. The comparisons show that the newly constructed global hmF2 model can reproduce reasonably well the observations and perform better than IRI-ITU-R model. (C) 2013 COSPAR. Published by Elsevier Ltd. All rights reserved.

In the present work we model the global ionospheric total electron content (TEC) with the analysis of empirical orthogonal functions (EOF). The obtained statistical eigen modes, which makeup the modeled TEC, consist of two factors: the eigen vectors mapping TEC patterns at latitude and longitude (or local time LT), and the corresponding coefficients displaying the TEC variations in different time scales, i.e., the solar cycle, the yearly (annual and semiannual) and the diurnal universal time variations. It is found that the EOF analysis can separate the TEC variations into chief processes and the first two modes illustrate the most of the ionospheric climate properties. The first mode contains both the semiannual component which shows the semiannual ionospheric anomaly and the annual component which shows the annual or non-seasonal ionospheric anomaly. The second mode contains mainly the annual component and shows the normal seasonal ionospheric variation at most latitudes and local time sectors. The annual component in the second mode also manifests seasonal anomaly of the ionosphere at higher mid-latitudes around noontime. It is concluded that the EOF analysis, as a statistical eigen mode method, is resultful in analyzing the ionospheric climatology hence can be used to construct the empirical model for the ionospheric climatology.

Global modeling of M(3000)F2 and hmF2 based on three alternative EOF (empirical orthogonal function) expansion methods is described briefly. Data used for the model construction is the monthly median hourly values of M(3000)F2 from the ionosonde/digisonde stations distributed around the world for the period of 1975–1985 and the hmF2 data of the same period converted from the measured M(3000)F2 based on the strong anti-correlation existing between them. Independent data of a low (1965) and a high (1970) solar activity year are used to validate the three alternative models based on different EOF expansion methods. Comparisons between the modeled results and observed data for both the low (1965) and high (1970) solar activity years showed good agreement for both M(3000)F2 and hmF2 parameters. Statistical analysis on the differences between model values and observed data showed that all the three alternative models (Model A, B and C) based on the different EOF expansion methods have better agreement with the observed data than the models currently used in IRI. All three alternative EOF based models have almost the same accuracy. Discussion on the preference of the three alternative EOF based models is given.

The present work studies the correlation relationship between the longitudinal ionospheric structure of wave number 4 (WN4) and the upper atmospheric tide of nonmigrating tidal mode DE3 (diurnal eastward wave number 3). Global ionospheric maps produced by the Jet Propulsion Laboratory were used to deduce the latitudinal integration of total electron content in the low‐latitude ionosphere, and TIDI/TIMED observations were used to retrieve the atmospheric zonal and meridional winds. By applying Fourier filtering and fitting techniques, the WN4 wave and DE3 tidal components are derived from the ionospheric and upper atmospheric observations, respectively. We found that the observed WN4 wave and DE3 zonal wind components experience very similar annual and interannual variations, but the DE3 meridional wind component behaves in a quite different manner. Both WN4 and DE3 zonal winds are very intense during northern summer and autumn; they also appear in the later spring, but tend to vanish in winter. Their amplitudes increase as the solar activity decreases, and both are stronger in the quasi‐biennial oscillation (QBO) eastward wind phase than in the westward phase. At the same time, the DE3 meridional wind likes to occur only in winter and seems not change with solar activity and QBO phase. We further studied the correlation between the WN4 wave and the two wind components of the DE3 tide. We found that the cross‐correlation coefficient between the WN4 wave and the DE3 zonal wind is much larger, while that between the WN4 wave and the DE3 meridional wind is relatively smaller. Such different correlations are attributed to the different latitudinal symmetry of different DE3 wind components. The DE3 zonal wind is likely in latitudinally symmetric tidal mode; hence, it can efficiently affect the F region ion drifts. In contrast, the meridional wind is mainly in antisymmetric mode and thus seldom affects the ionospheric drifts. The present results support the suggestion that the longitudinal WN4 structure in the ionospheric F region originates from the symmetric modes, mainly the zonal wind component, of the upper atmospheric nonmigrating tidal mode DE3 in the ionospheric E region.

The ionospheric F2 peak height hmF2 is an important parameter that is much needed in ionospheric research and practical applications. In this paper, an attempt is made to develop a global model of hmF2. The hmF2 data, used to construct the global model, are converted from the monthly median hourly values of the ionospheric propagation factor M(3000)F2 observed by ionosondes/digisondes distributed globally, based on the strong anti-correlation existed between hmF2 and M(3000)F2. The empirical orthogonal function (EOF) analysis method, combined with harmonic function and regression analysis, is used to construct the model. The technique used in the global modelling involves two layers of EOF analysis of the dataset. The first layer EOF analysis is applied to the hmF2 dataset which decomposed the dataset into a series of orthogonal functions (EOF base functions) Ek and their associated EOF coefficients Pk. The base functions Ek represent the intrinsic characteristic variations of the dataset with the modified dip latitude and local time, the coefficients Pk represents the variations of the dataset with the universal time, season as well as solar cycle activity levels. The second layer EOF analysis is applied to the EOF coefficients Pk obtained in the first layer EOF analysis. The coefficients Ak, obtained in the second layer EOF analysis, are then modelled with the harmonic functions representing the seasonal (annual and semi-annual) and solar cycle variations, with their amplitudes changing with the F10.7 index, a proxy of the solar activity level. Thus, the constructed global model incorporates the geographical location, diurnal, seasonal as well as solar cycle variations of hmF2 through the combination of EOF analysis and the harmonic function expressions of the associated EOF coefficients. Comparisons between the model results and observational data were consistent, indicating that the modelling technique used is very promising when used to construct the global model of hmF2 and it has the potential of being used for the global modelling/mapping of other ionospheric parameters. Statistical analysis on model-data comparison showed that our constructed model of hmF2, based on the EOF expansion method, compares better with the observational data than the model currently used in the International Reference Ionosphere (IRI) model.

In this paper, latitudinal profiles of the vertical total electron content (TEC) deduced from the dual-frequency GPS measurements obtained at ground stations around 120°E longitude were used to study the variability of the equatorial ionization anomaly (EIA). The present study mainly focuses on the analysis of the crest-to-trough TEC ratio (TEC-CTR) which is an important parameter representing the strength of EIA. Data used for the present study covered the time period from 01 January, 1998 to 31 December, 2004. An empirical orthogonal function analysis method is used to obtain the main features of the TEC-CTR’s diurnal and seasonal variations as well as its solar activity level dependency. Our results showed that: (1) The diurnal variation pattern of the TEC-CTR at 120°E longitude is characterized by two remarkable peaks, one occurring in the post-noon hours around 13–14LT, and the other occurring in the post-sunset hours around 20–21LT, and the post-sunset peak has a much higher value than the post-noon one. (2) Both for the north and south crests, the TEC-CTR at 120°E longitude showed a semi-annual variation with maximum peak values occurring in the equinoctial months. (3) TEC-CTR for the north crest has lower values in summer than in winter, whereas TEC-CTR for the south crest does not show this ‘winter anomaly’ effect. In other words, TEC-CTR for both the north and south crests has higher values in the northern hemispheric winter than in the northern hemispheric summer. (4) TEC-CTR in the daytime post-noon hours (12–14LT) does not vary much with the solar activity, however, TEC-CTR in the post-sunset hours (19–21LT) shows a clear dependence on the solar activity, its values increasing with solar activity.

We collected the ionospheric electron density (Ne) profiles from the FORMOSAT‐3/COSMIC (F3/C) radio occultation measurements to investigate the seasonal behaviors of daytime Ne in the altitude range of 200–560 km. Harmonic analysis of the Ne at different altitudes provides unprecedented detail of the seasonal behaviors of Ne at low solar activity (LSA). Global maps of seasonal harmonic components indicate that there are strong annual and semiannual variations in daytime Ne, which have distinct latitudinal and altitudinal dependency. The semiannual component predominates over the annual variation in the equatorial regions and at high latitudes in the East Asian and South Atlantic sectors at low altitudes, and at higher altitudes the semiannual component predominates in the equatorial region, but recedes in other regions. The semiannual variation peaks in equinoctial months in most regions, while it has maxima in solstice months, first in the South Pacific region (around 30°S, 120°W) at 250 km altitude and expanding over the South Pacific and South Atlantic oceans at higher altitudes. Moreover, there is a region around 45°S, 30°W with a dominant semiannual component, moving toward east‐north with increasing altitude in the range of 200–270 km. These two interesting features are novel but are not reported yet. The relative amplitude of the annual component of Ne has hemispheric asymmetry, which is prominent at high altitudes in the Southern Hemisphere. The winter/seasonal anomaly widely exists in the Northern Hemisphere and southern low latitudes and in Indian Ocean region at low altitudes but gradually disappears at higher altitudes. Further, in equatorial regions, a new finding is the obvious wave‐like pattern in the longitudinal structure of the amplitudes of seasonal harmonic components in equatorial regions, which supports possible couplings of sources with lower atmospheric origins in the longitudinal variations of Ne.

On the basis of the f(o) F-2 observed from four ionosonde stations in the East-Asian sector during 515 magnetic storms from 1957 to 2006, we statistically analysis the types, the onset times and the time delay of ionospheric storms to reveal the distributions of the ionospheric response during storms related to geomagnetic latitude, season and local time. The result shows that, the negative responses prevail at mid latitude, whereas the positive responses prevail at low latitude. There are more negative storms in summer and more positive storms in winter. In equinox, the distribution of ionospheric storms shows latitudinal difference. At mid latitude, most negative phase onsets are within the night to early morning sector, and they are rarely occurred in the noon and afternoon sectors. At low latitude, positive phase onsets commence most frequently in the local daytime sector, also they commence a lot at 18 similar to 21 LT. The average time delay for ionospheric positive storms is mostly within 10 hours, while it is longer than 10 hours for negative storms, and the time delay is significantly shorter for mid latitude than for low latitude. The time delay has large dependence on the local time of MPO. The time delay of positive response is low for daytime MPO and high for nighttime MPO, whereas the opposite applies for negative response. But there is no significant relationship between the time delay and the intensity of magnetic storms.

The global ionospheric maps (GIMs) produced by JPL are used to investigate the longitudinal structure of the low latitude ionosphere. As a proxy of the ionization parameter at low latitudes, the latitudinally integrated total electron content (ITEC) is first extracted from low latitude GIMs and then Fourier filtered to obtain the wavenumber‐4 components. We then study in detail the diurnal, seasonal and solar cycle variations of the wave patterns. It is found that the wavenumber‐4 patterns are intense and well developed in boreal summer and early boreal autumn, but quite weak in boreal winter. This seasonal variation is consistent with that of the zonal wind of the non‐migrating tide mode DE3. We also found that the wavenumber‐4 patterns shift eastward with a shifting speed that is smaller in daytime than at night. This is attributed to the contribution of both the eastward propagation of DE3 in E‐region and the zonal E × B ion drifts in F‐region. Our results support the suggestion that the longitudinal wavenumber‐4 structure of the low latitude ionosphere should be originated from the non‐migrating tide mode DE3.

The enhancement of electron concentrations in the ionosphere before geomagnetic storms is one of the open questions. Using ionosonde observations and total electron content (TEC) from Global Positioning System (GPS) measurements along longitude 120°E, we analyzed three low latitude pre‐storm enhancement events that occurred on 21 April (day 111) 2001, 29 May (day 149) 2003, and 22 September (day 265) 2001, respectively, in the Asia/Australia sector. All three events (and other two cases on 9 August 2000 and 10 May 2002) show quite similar features. The strong prestorm enhancements during these events are simultaneously presented in foF2 and TEC and enhancements have latitudinal dependence, tending to occur at low latitudes with maxima near the northern and southern equatorial ionization anomaly (EIA) crests and depletions in the equatorial region. This is quite different from what reported by Burešová and Laštovička (2007) for middle latitudes. They found no systemic latitudinal dependence in prestorm enhancements over Europe. It is argued that solar flares are not the main drivers for the enhancements, at least for low‐latitude events. Main features of low‐latitude prestorm enhancements do not coincide with the solar flare effects. We postulate that the vertical plasma drift or zonal electric field is a likely cause for the low‐latitude prestorm enhancements. Its existence is supported by the facts of stronger EIA, the latitudinal coverage of the enhancements as well as the lift of the F layer peak height at an equatorward station during the prestorm enhancements. Moreover, the behaviors of hmF2 at low latitudes during the prestorm enhancements may possibly be explained in terms of the coupling nature of parallel and perpendicular dynamics at low latitudes (see, e.g., Behnke and Harper, 1973; Rishbeth et al., 1978).

An empirical orthogonal function (EOF) analysis, combined with a regression analysis, is conducted to construct an empirical model for the ionospheric propagation factor M(3000)F2. First, a single station model is constructed using monthly median hourly values of M(3000)F2 data observed at Wuhan Ionospheric Observatory (geographic 114.4°E, 30.6°N; 45.2°dip) during the years of 1957–1991 for demonstrating the modeling technique based on EOF expansion and regression analysis of the EOF coefficients. The constructed climatological model incorporates the diurnal, seasonal as well as solar‐cycle variations of M(3000)F2. A comparison between the observational results and the modeled ones showed good agreement. Then, an attempt is made to model global M(3000)F2 data using data from stations distributed around the world. Our preliminary result showed that the modeling technique based on EOF expansion, which is combined with regression analysis of the EOF coefficients as described in this paper, is very promising when used in global modeling and is worthwhile to investigate further.

TIME-IGGCAS(Theoretical Ionospheric Model of the Earth in Institute of Geology and Geophysics,Chinese Academy of Sciences)模式是我们在前人工作的基础上完善的一个中低纬理论电离层模式.本文把该模式的结果与其他一些有代表性的经验模式和多种观测数据作了详细的对比.比较结果表明:TIME-IGGCAS模式模拟的电子浓度、电子离子温度在数量级上均与经验模型和观测符合得较好,在地方时变化、纬度变化、季节变化这些变化形态上也符合得较好,并且模式能很好地模拟出赤道异常、冬季异常和半年异常这些电离层异常,这为我们进一步开发电离层数据同化模式奠定了良好的基础.无论是与经验模式还是与观测相比,TIME-IGGCAS模式均低估了电子温度而高估了离子温度,模式在日出日落时段和在低高度模拟的偏差较大,这些结果为我们以后进一步完善模式、改善模式的模拟能力提供了参考.

In this paper, data of (B0, B1) parameters deduced from the electron density profiles that are inverted from the ionograms recorded at Hainan (19.4°N, 109.0°E), China during a three year period from March 2002 to February 2005 are used to study the diurnal and seasonal variation of (B0, B1) parameters at low latitude. The observational results are compared with the IRI2001 model predictions. Variability study of (B0, B1) in terms of percentage ratio of the inter-quartiles to the median values and correlative analysis between (B0, B1) parameters and other ionospheric characteristics such as hmF2 and M(3000)F2 are also made. Our present study showed that: (1) for daytime hours, the IRI2001 model results with new table option (B0_Tab) is in a better agreement with the observational results (B0_Obs) than the IRI2001 model results with Gulyaeva option (B0_Gul) for summer season, whereas B0_Gul is in a better agreement with B0_Obs than B0_Tab for winter season. For nighttime, in general, B0_Gul is in a better agreement with B0_Obs than B0_Tab. For other occasions, both B0_Tab and B0_Gul showed some systematic deviations from the observational ones. Moreover, the deviations of B0_Tab and B0_Gul from B0_Obs showed opposite trends; (2) the monthly upper (lower) quartiles of (B0, B1) parameter showed a good linear relationship with the monthly median values, this makes it possible to do the regression analysis between the monthly upper (lower) quartiles and the monthly median values, which can give a measure of the variability of these parameters. In terms of the percentage ratio of the inter-quartiles to the median values, the variability of B0 showed a diurnal variation ranging between 22% and 36% with maximum value occurring at pre-sunrise hours, whereas the variability of B1 showed a diurnal variation ranging between 15% and 30% with higher value by daytime than at night; (3) B0 shows high linear correlative relationships with hmF2 and M(3000)F2 for most of the local time period of a day except for a few hours around midnight, whereas B1 showed high linear correlations with B0, hmF2 for daytime hours, but not for nighttime hours. This suggests that it maybe is possible to obtain the synthetic database of (B0, B1) parameter or to construct the model of (B0, B1) using database of hmF2 or M(3000)F2 which is much easier to obtain from experimental measurements.