Concentric traveling ionosphere disturbances (CTIDs) in total electron content triggered by Super Typhoon Meranti on 13 September 2016 are detected by using the ground‐based Global Navigation Satellite Systems network in Taiwan. The CTIDs emanated outward before the typhoon landfall and lasted for more than 10 h. The characteristics of CTIDs agree with the gravity wave theory and exhibit spatial and temporal scales in wave periods of ~8–30 min, horizontal wavelengths of ~160–200 km, and horizontal phase velocities of ~106–220 m/s. We also observe the CTIDs showing the stationary wave character. Broad spectra of CTIDs are excited after the rainbands of typhoon impinged on Central Mountain Range of Taiwan. The ray‐tracing technique confirms that the CTIDs were excited by convective clouds, spiral rainbands, and the eyewall of Typhoon Meranti. This study provides new evidence of typhoon‐induced concentric gravity waves in the ionosphere.

Two remarkable typhoon‐induced traveling ionospheric disturbances (TIDs) with concentric and northwest‐southeast (NW‐SE) alignments, respectively, associated with concentric gravity waves (CGWs) and ionosphere instabilities possibly seeded by CGWs, were observed in total electron content (TEC) derived from ground‐based Global Navigation Satellite System networks in Taiwan and Japan when the Category 5 Super Typhoon Nepartak approached Taiwan on 7 July 2016. The concentric TIDs (CTIDs) first appear with horizontal phase velocities of ~161–200 m/s, horizontal wavelengths of ~160–270 km, and periods of ~15–22 min during 08:00–11:20 UT. Following the CTIDs, the NW‐SE aligned nighttime medium‐scale TIDs (MSTIDs) are formed on the west edge of the CTIDs over the Taiwan Strait during 11:30–14:00 UT. It is suggested that the MSTIDs are produced by the electrodynamical coupling of Perkins instability and CGW‐induced polarization electric fields. This study proposes connections of typhoon‐induced CTIDs and subsequently occurring MSTIDs in the low‐latitude ionosphere.

We report the first observation of concentric traveling ionospheric disturbances (CTIDs) triggered by the launch of a SpaceX Falcon 9 rocket on 17 January 2016. The rocket‐triggered ionospheric disturbances show shock acoustic wave signature in the time rate change (time derivative) of total electron content (TEC), followed by CTIDs in the 8–15 min band‐pass filtering of TEC. The CTIDs propagated northward with phase velocity of 241–617 m/s and reached distances more than 1000 km away from the source on the rocket trajectory. The wave characteristics of CTIDs with periods of 10.5–12.7 min and wavelength ~ 200–400 km agree well with the gravity wave dispersion relation. The optimal wave source searching and gravity wave ray tracing technique suggested that the CTIDs have multiple sources which are originated from ~38–120 km altitude before and after the ignition of the second‐stage rocket, ~200 s after the rocket was launched.

The main purpose of this paper is to investigate the effects of rapid assimilation‐forecast cycling on the performance of ionospheric data assimilation during geomagnetic storm conditions. An ensemble Kalman filter software developed by the National Center for Atmospheric Research (NCAR), called Data Assimilation Research Testbed, is applied to assimilate ground‐based GPS total electron content (TEC) observations into a theoretical numerical model of the thermosphere and ionosphere (NCAR thermosphere‐ionosphere‐electrodynamics general circulation model) during the 26 September 2011 geomagnetic storm period. Effects of various assimilation‐forecast cycle lengths: 60, 30, and 10 min on the ionospheric forecast are examined by using the global root‐mean‐squared observation‐minus‐forecast (OmF) TEC residuals. Substantial reduction in the global OmF for the 10 min assimilation‐forecast cycling suggests that a rapid cycling ionospheric data assimilation system can greatly improve the quality of the model forecast during geomagnetic storm conditions. Furthermore, updating the thermospheric state variables in the coupled thermosphere‐ionosphere forecast model in the assimilation step is an important factor in improving the trajectory of model forecasting. The shorter assimilation‐forecast cycling (10 min in this paper) helps to restrain unrealistic model error growth during the forecast step due to the imbalance among model state variables resulting from an inadequate state update, which in turn leads to a greater forecast accuracy.

In this study, we develop a three-dimensional ionospheric tomography with the ground-based global position system (GPS) total electron content observations. Because of the geometric limitation of GPS observation path, it is difficult to solve the ill-posed inverse problem for the ionospheric electron density. Different from methods given by pervious studies, we consider an algorithm combining the least-square method with a constraint condition, in which the gradient of electron density tends to be smooth in the horizontal direction and steep in the vicinity of the ionospheric F2 peak. This algorithm is designed to be independent of any ionospheric or plasmaspheric electron density models as the initial condition. An observation system simulation experiment method is applied to evaluate the performance of the GPS ionospheric tomography in detecting ionospheric electron density perturbation at the scale size of around 200 km in wavelength, such as the medium-scale traveling ionospheric disturbances.