Global equatorial plasma bubble growth rates using ionosphere data assimilation

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. Key Points Ionosphere data assimilation is used for the first time to compare the plasma bubble growth rate and occurrence Assimilated growth rates agree remarkably with irregularities indicated by GPS‐ROTI and 630.0 nm all‐sky images The improvement of zonal electric field in the assimilation mostly contributes to forecasting realistic growth rates