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.

Abstract. This paper presents a two-dimensional structure of the shock wave signatures in ionospheric electron density resulting from a rocket transit using the rate of change of the total electron content (TEC) derived from ground-based GPS receivers around Japan and Taiwan for the first time. From the TEC maps constructed for the 2009 North Korea (NK) Taepodong-2 and 2013 South Korea (SK) Korea Space Launch Vehicle-II (KSLV-II) rocket launches, features of the V-shaped shock wave fronts in TEC perturbations are prominently seen. These fronts, with periods of 100–600 s, produced by the propulsive blasts of the rockets appear immediately and then propagate perpendicularly outward from the rocket trajectory with supersonic velocities between 800–1200 m s−1 for both events. Additionally, clear rocket exhaust depletions of TECs are seen along the trajectory and are deflected by the background thermospheric neutral wind. Twenty minutes after the rocket transits, delayed electron density perturbation waves propagating along the bow wave direction appear with phase velocities of 800–1200 m s−1. According to their propagation character, these delayed waves may be generated by rocket exhaust plumes at earlier rocket locations at lower altitudes.

[1] The global ionospheric response to a stratospheric sudden warming (SSW) is studied using three-dimensional electron density maps derived from radio occultation observations of FORMOSAT-3/COSMIC during the 2009 SSW periods. Results show that the ionospheric electron density at EIA crests exhibit a morning/early afternoon increase followed by an afternoon decrease and an evening increase, indicative of a semidiurnal component during the SSW period, which is consistent with recent studies. The latitude-altitude electron density slice maps show that the SSW related modifications of the equatorial plasma fountain interact with the existing summer-to-winter neutral winds and resulting in a north-south asymmetry. The global ionospheric response shows a clear longitudinal dependence in the equatorial plasma fountain enhancement during morning/early afternoon, inferred from the duration of the equatorial ionization anomaly (EIA) enhancement. Following the enhancement, prominent global EIA reductions resulting from the equatorial plasma fountain weakening in the afternoon sector are seen. The ionospheric response to the 2009 SSW event is also compared with the usual seasonal variation during January-February 2007. Instead of showing the electron density increase in the northern hemisphere and decrease in the southern hemisphere as the usual seasonal variation does, the SSW period ionosphere shows prominent global electron density reductions in the afternoon period during the 2009 SSW event.

The ionospheric plasma disturbances during a severe storm can affect human activities and systems, such as navigation and HF communication systems. Therefore, the forecast of ionospheric electron density is becoming an important topic recently. This study is conducted with the ionospheric assimilation model by assimilating the total electron content observations into the thermosphere‐ionosphere coupling model with different high‐latitude ionospheric convection models, Heelis and Weimer, and further to forecast the variations of ionospheric electron density during the 2015 St. Patrick's Day geomagnetic storm. The forecast capabilities of these two assimilation models are evaluated by the root‐mean‐square error values in different regions to discuss its latitudinal effects. Results show the better forecast in the electron density at the low‐latitude region during the storm main phase and the recovery phase. The well reproduced eastward electric field at the low‐latitude region by the assimilation model reveals that the electric fields may be an important factor to have the contributions on the accuracy of ionospheric forecast.

Flux tube integrated Rayleigh‐Taylor instability growth rates computed by using the results of ionosphere data assimilation are used for the first time to investigate global plasma bubble occurrence. The study is carried out by assimilating total electron content measurements using ground‐based Global Positioning System (GPS) receivers into thermosphere ionosphere electrodynamic general circulation model, and the growth rates are calculated by using standalone model run without assimilation (control run) as well as using prior (or forecast) state output of the assimilation run. The growth rates are compared with the rate of change of total electron content index (ROTI), estimated from global network of GPS receivers, as well as all‐sky airglow observations carried out over Taiwan on the nights of 16 and 17 March 2015. In contrast to the growth rates using the control run, results using data assimilation show remarkable agreement with the ROTI. Further, the all‐sky images reveal intense plasma bubbles over Taiwan on the night of 16 March, when the corresponding assimilated growth rate is also pronounced. Similarly, the absence of plasma bubbles in the all‐sky images on the night of 17 March (St. Patrick's Day storm) is supported by smaller growth rates predicted by the assimilation model. Significant improvements in the calculated growth rates could be achieved because of the accurate updating of zonal electric field in the data assimilation forecast. The results suggest that realistic estimate or prediction of plasma bubble occurrence could be feasible by taking advantage of the data assimilation approach adopted in this work.