Ionospheric data assimilation with thermosphere‐ionosphere‐electrodynamics general circulation model and GPS‐TEC during geomagnetic storm conditions

Abstract

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.

Similarity and differences in morphology and mechanisms of the <i>fo</i>F2 and TEC disturbances during the geomagnetic storms on 26–30 September 2011

“…Figure 1 Hairston et al (2013), Wang et al (2013), Kotova et al (2015), Klimenko et al (2015a), Solomentsev et al (2015), and Chen et al (2016).…”

The impact of FORMOSAT-5/AIP observations on the ionospheric space weather

“…In this study, O + fluxes along the simulated orbit of FS-5 and the ground-based GPS-IEC from 100 -2000 km altitude are calculated with SAMI3 as synthetic OSSE observations. The ionospheric data assimilation system using TIE-GCM developed by Chen et al (2016) is employed with 1-hr assimilation cycling. The O + fluxes expected to be observed by FS-5/AIP are assimilated in the assimilation system every 1 minute, which means there are 60 in-situ observation points along the satellite orbit for each assimilation cycle.…”

“…Noted that the electron density above the upper boundary in the TIE-GCM is extended using the natural exponential function up to 2000 km (cf. Chen et al 2016). The IEC difference (bottom panel of Fig.…”

“…In this paper the ionospheric data assimilation system algorithm developed by Chen et al (2016) (Lin et al 2017). From AIP measurements, we can estimate the O + fluxes for the ionosphere assimilation model.…”

“…This approach has been applied to assimilate thermospheric/ionospheric observations into a three-dimensional global thermosphereionosphere coupled model, National Center for Atmospheric Research Thermosphere-Ionosphere-Electrodynamics General Circulation Model (NCAR TIE-GCM) (Matsuo and Araujo-Pradere 2011;Lee et al 2012Lee et al , 2013Chartier et al 2013Chartier et al , 2016Hsu et al 2014;Chen et al 2016). Chen et al (2016) successfully constructed a module capable of assimilating ground-based GPS total electron content (TEC) observations to this ionospheric data assimilation system. They employed this assimilation system to investigate the ionospheric features and further examined its forecast capability during the geomagnetic storm period.…”