Lightning-generated whistlers (LGWs) carry information about ionospheric electron density due to the dispersion effect in the ionosphere and thus can be utilized as an inexpensive medium to detect the ionosphere. In this paper, data assimilation technology is adopted as the ionospheric inversion method based on the relationship between the dispersion of LGWs and ionospheric electron density. Using LGWs observed by the China Seismo-Electromagnetic Satellite, a three-dimensional electron density assimilation model is constructed for the central eastern regions and surrounding seas of China. After assimilation, the discrepancy between the VTEC of the background model and the true value is significantly reduced under both quiet and magnetic storm conditions. The root mean square error (RMSE) of VTEC decreases by 56.06% under quiet conditions and 46.81% under magnetic storm conditions. Additionally, the model effectively corrects the electron density profile, improving the F2 layer’s peak electron density accuracy by over 50%. When applied to the summer of 2021, the RMSE of assimilated VTEC decreases to below 3 TECU in all cases. The mean and standard deviation of the RMSE after assimilation are 2.4631 TECU and 0.3048 TECU respectively, demonstrating the model’s accuracy and stability. The method proposed in this paper fills a gap in the research domain of 3-D electron density inversion by LGWs and provides valuable observations for ionospheric regions that are difficult to detect by artificial emission signals.

Precipitable water vapor (PWV) retrieved from Global Navigation Satellite System (GNSS) has been successfully applied in rainfall forecast. This article shifts to a new focus, aiming at nowcasting lightning, for its relatively scant GNSS-PWV investigation. Unlike previous studies that mainly explored statistical correlations between PWV and lightning, this approach integrates GNSS-PWV and other meteorological parameters with advanced automated machine-learning algorithms to accurately predict lightning occurrences with a lead-time up to 30 min. In this article, the relationship between lightning occurrences and PWV variations is first examined through comprehensive statistical analysis. Next, a machine-learning-based lightning nowcasting model is established in this study, with the input of GNSS-PWV and common meteorological parameters. The training and test datasets are sampled every 10 min from seven collocated GNSS stations and automatic weather stations (AWSs) along with the lightning location information during the period from 2018 to 2022 in Hong Kong. A comprehensive evaluation is conducted on the performance of the lightning nowcasting model. Results indicate that the proposed model possesses convincingly more excellent performances over four evaluation metrics: probability of detection (POD, 89%), false alarm ratio (FAR, 30%), threat score (TS, 0.64), and Heidke skill score (HSS, 0.77). It is also revealed that this model achieves impressive innovativeness, performance, and competitive advantages, compared with other existing methods and previous lightning forecast models.

Global Navigation Satellite System (GNSS) ionospheric tomography is a typical ill-posed problem. Joint inversion with external observation data is one of the effective ways to mitigate the problem. In this article, by fusing 3-D multisource ionospheric data, and improving the stochastic model, an improved GNSS tomographic algorithm MFCIT [computerized ionospheric tomography (CIT) using mapping function] is presented. The accuracy of the algorithm is validated by selected data under different geomagnetic and solar conditions acquired in Europe. The results show that the estimated, statistically significant uncertainty for each of the layers is about 0.50-3.0TECU, with the largest absolute error within 6.0TECU. The advantage of the MFCIT is that it is based on the Kalman filter, which enables efficient near real-time 3-D monitoring of ionosphere. The temporal resolution can reach ~1 min level. Here, we apply the ionospheric tomography inversion to the magnetic storm on January 7, 2015, in the European region, and quantified the evolution of the storm. The results show that the difference of the core region between the MFCIT and CODE GIM is less than 1TECU. More importantly, during the initial phase of the storm, when the ionospheric disturbance is not evident in the single layer CODE GIM model, the MFCIT shows obvious positive disturbances in the upper ionosphere, although there is no disturbance in the F2 layer. The MFCIT further tracks the evolution of the magnetic storm that the ionospheric disturbance expands from the upper to the lower ionosphere layers, and at UT12:00, the disturbance continues to spread to the F2 layer.

Using the Global Navigation Satellite System (GNSS) differenced total electron content (dTEC) series, the traveling ionosphere disturbances (TIDs) of 22 typhoons registered in Taiwan/Japan between 2013 and 2016 were studied. The horizontal speed of the first TID during a typhoon landing can be estimated by a two-station method with the ionosphere anomaly indicator in total electron count units (TECUs) (|dTEC| ≥ 0.15 TECU). The horizontal speed of the TIDs was from 155 to 210 m/s and with an average speed of 168.70 m/s. The estimated TID speeds of Typhoons Soudelor (205.93 m/s) and Megi (158.47 m/s) are not consistent with each other, even though they had very similar trajectories when cross through Taiwan Island. Moreover, the propagation velocity of the typhoon ionospheric anomaly showed a significant positive correlation ( r = 0.78, α = 0.05) with the change rate of the typhoon central air pressure and a negative correlation ( r = -0.52, α = 0.05) with the central pressure before landing. Gravity waves were generated by land friction, terrain blocking, and strong wind shear transport energy into the atmosphere from the near surface to the mesosphere and thermosphere, which is the main cause of ionosphere disturbances during typhoon landing.

In order to improve the accuracy of the International Reference Ionosphere (IRI)-2016 model for application in the Antarctic region, total electron content (TEC) data from the Global Navigation Satellite Systems (GNSS) observation data in 2018 are assimilated into the IRI-2016 model by updating the effective ionospheric parameter, IG12 index on a daily basis. The functional relationship between the IG12 index and the longitude, latitude, and the day of year (DOY) is fitted by using the spherical crown harmonic function and the polynomial, and finally establish an updated experiential model of IG12 indices over the Antarctic region. Conclusions that were reached were: 1) the updated IG12 index varies greatly over different geographical locations and 2) it is also apparent that the accuracy of the IRI-2016 model is worse in the perpetual night than that in the perpetual day. In order to verify our method, the TEC calculated by the IRI-2016 model driven by the updated IG12 index and that calculated by the original IRI-2016 model are compared with the GNSS-TEC, and the results show that the updated IRI-2016 model has improved the accuracy of the BIAS and root mean square (RMS) of the TEC calculation by 97% and 87%, respectively, on the fitting moments, while 75% and 54% on the predicting moments. In addition, compared with the original IRI-2016 model, it is found that the updated IRI-2016 model improves the accuracy of the NmF2 calculation by approximately 23% on average for the fitting time and 8% for the predicting time.

The observations of the Wuhan mesosphere, stratosphere, and troposphere radar with different tilted angles and observational modes are used to study the aspect sensitivity of the radar echoes and discuss the echo mechanism in the lower thermosphere, mesosphere, lower stratosphere, and troposphere. This letter indicates that: 1) the variation of radar echoes with different tilted angles is more obvious in the troposphere than that in the lower thermosphere, mesosphere, and lower stratosphere; 2) the values of the aspect sensitivity of radar echoes in the tropopause region and the mesopause region are smaller than that in the other region, which shows the difference of the echo mechanism; 3) the radar echo mechanism has the obvious spatial direction difference (S-N and E-W) in the mesosphere and lower stratosphere. Meanwhile, in the lower thermosphere, the sudden probability of radar enhanced echoes is larger, which may be related to the electronic thermal radiation, the scattering of the electron group, meteor trails, or the breaking of the gravity waves; and 4) in the troposphere and the lower stratosphere, the values of the aspect sensitivity increase with the increase of the tilted angles at all most height regions. However, the variations of the values of the aspect sensitivity are not monotonic in the lower thermosphere and mesosphere, which is much different from that in the troposphere and the lower stratosphere.

We report a new observation of daytime ionospheric irregularities on December 27, 2009, at low latitudes in China using multistatic HF radar. The transmitter, with a horizontal polarization log-periodic antenna pointing westward, is located at Wanning (18.97° N, 110.50° E, dip angle 19°). Three separate receivers are in Sanya (18.20° N, 109.49° E), Qiongzhong (19.04° N, 109.77° E), and Tunchang (19.42° N, 110.13° E). Doppler spectra, frequency power spectra, and wavenumber power spectra from the three receivers were calculated. The main features of these observations are: 1) the irregularities observed at 12:10 (LT) had typical lengths on the scale of tens of meters and the altitude was in the range of 105-175 km, which is located in the E region and bottom of the F region; 2) the power distributions from the three receivers are consistent with the irregularities being field aligned; and 3) features consistent with a cascade of irregular spatial scales were observed. We suggest that the observed irregularity could be due to the intermediate layer modulated by electrodynamic instability.

We present the observational evidence of Eand Fregion field-aligned irregularities (FAIs), nighttime medium-scale traveling ionospheric disturbances (MSTIDs), and a sporadic E (ES)-layer using the Wuhan very-high-frequency (VHF) coherent scatter radar, Wuhan Global Navigation Satellite System (GNSS) network, and Wuhan ionosonde. We observed simultaneously E and F FAIs by VHF radar and the ES-layer and spread-F by Wuhan ionosonde. We also observed MSTIDs using the Wuhan GNSS network in a southwestward direction of propagation and horizontal propagation velocity of less than 180 m/s, for a period of ~33 min. Simultaneous observations of an ES-layer and FAIs in the E-region and FAIs in the F-region suggested the existence of an electrodynamic coupling between the E and F regions in the midand low-latitude nighttime ionosphere. A polarized electric field associated with nighttime MSTIDs can generate the uplift movements of the F-region's electron density. This uplift effect consequently can excite the gradient drift instability (GDI) with an accompanying enhanced vertical gradient of the F-layer's electron density. Our results indicated that the F-region MSTIDs excited by Perkins instability might be further modulated by the E × B effect and subsequently can evolve to spread-F like FAIs. Our observational investigation provided the first evidence of the full dynamics and links among different ionospheric disturbances in a midand low-latitude nighttime region of China.

Convection is an important source to excite gravity waves. But the activity characteristics of the convection are hard to research, because it is transient and localized. This paper utilizes the five beams operated by mesosphere-stratosphere- troposphere radar to study the radial movements before, during, and after the small-scale convection. The Doppler spectra of radar echoes during the convection are evidently different from that in the clear weather. The strong updrafts (~5.1 m · s-1) and downdrafts (~2.4 m · s-1) make the turbulent motion compositions more complex, so the radial Doppler velocity and Doppler widths of five beams are almost significantly different at the same height. The characteristics of gravity waves are detected by using the quasi-monochromatic inertia gravity wave model. The results indicate that: 1) the kinetic energies of the IGWs during the convection are more powerful than that before and after the convection, and the propagation directions of the IGWs during the convection are also different to that before and after the convection and 2) the propagation parameters of the IGWs in different regions are also different during the convection, which means that the cold zone is at south and the warm zone is at north for this convection case.

By using the 2015-2016 data set of newly built Wuhan very high-frequency (VHF) radar, we investigate the occurrence of E-region field-aligned irregularities (FAIs) in mid-latitude China region for the first time. Wuhan E-region FAIs present the strongest occurrence of quasi-periodic (QP) echoes at postsunset period in the height range of 100-120 km and moderate occurrence of continuous echoes at postsunrise period in the height range of 90-100 km. Characteristics including temporal and altitudinal distribution, Doppler spectra and period of QP echoes are presented from a statistical point of view. We find that E-region FAIs observed by Wuhan VHF radar show strong linkage with the concurrent sporadic E layer observed by ionosonde. In general, Doppler spectra present type 2 feature with velocity in the range of ±50 m/s and width less than 50 m/s. Our results also indicate that mid-latitude E-region FAIs are closely associated with Es layer. Several mechanisms were proposed to interpret the mid-latitude E-region FAIs; however, further investigation is required to understand the generation with different ionospheric background and irregularity types.

Purchasing behavior analysis plays a crucial role in pricing, recommendation, and market strategy designing. One of the fundamental questions that arises in purchasing behavior analysis is to understand, characterize and estimate purchasing capability. In this article, we investigate the patterns of purchasing capability from the perspective of network usage of smartphone consumers based on a large-scale usage detail records (UDRs). First, the purchasing capability of smartphone consumers are divided into three (high/middle/low) levels according to corresponding device retail price around observation period. Then we pairwise integrating interest and temporality information, and conduct a clustering analysis for each purchasing capability level users. Finally, the profile of each community is extracted by a visualization process. The learned patterns can not only illustrate how users behave on interest, but also describe their network usage preference on temporality, providing fine-granularity to understand the dynamics behind each purchasing capability group. Moreover, inspired by learned patterns, we find network usage distribution on temporality, spatiality and interest can serve as good indicators for estimating users purchasing capability. Our work has broad applicability in fields such as pricing, recommendation, and market strategy designing.

The Wuhan Ionospheric Oblique Backscattering Sounding System (WIOBSS) is a monostatic high-frequency sky-wave radar used for ionospheric remote sensing. The sweep frequency backscatter ionogram (SFBI) recorded by the WIOBSS contains both backscatter echo scattered by distant terrestrial surface and vertical incidence (VI) echo reflected by local ionosphere over the sounding station. The approach for SFBI inversion introduced in this letter requires input of leading edge and peak height derived from local VI echo. The final output of this SFBI inversion approach is the 2-D electron density distribution in a vertical plane aligned in the direction of sounding. In addition, the time and geographic variation of foF2 can be obtained from a series of SFBI inversion results. Two experiments have been utilized to validate the SFBI inversion approach, and the SFBI inversion results are found to be very close to the ionosonde data. The fast-converged feature of the approach makes it possible for applications in real time. The success of the SFBI inversion approach enables us to use the WIOBSS as a vehicle-mounted system to obtain ionosphere electron density profile over a large geographic area.