Assessing space weather modeling capability is a key element in improving existing models and developing new ones. In order to track improvement of the models and investigate impacts of forcing, from the lower atmosphere below and from the magnetosphere above, on the performance of ionosphere-thermosphere models, we expand our previous assessment for 2013 March storm event [Shim et al., 2018]. In this study, we evaluate new simulations from upgraded models (Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics (CTIPe) model version 4.1 and Global Ionosphere Thermosphere Model (GITM) version 21.11) and from NCAR Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X) version 2.2 including 8 simulations in the previous study. A simulation of NCAR Thermosphere-Ionosphere-Electrodynamics General Circulation Model version 2 (TIE-GCM 2) is also included for comparison with WACCM-X. TEC and foF2 changes from quiet-time background are considered to evaluate the model performance on the storm impacts. For evaluation, we employ 4 skill scores: Correlation coefficient (CC), root-mean square error (RMSE), ratio of the modeled to observed maximum percentage changes (Yield), and timing error(TE). It is found that the models tend to underestimate the storm-time enhancements of foF2 (F2-layer critical frequency) and TEC (Total Electron Content) and to predict foF2 and/or TEC better in the North America but worse in the Southern Hemisphere. The ensemble simulation for TEC is comparable to results from a data assimilation model (Utah State University-Global Assimilation of Ionospheric Measurement (USU-GAIM)) with differences in skill score less than 3% and 6% for CC and RMSE, respectively.

Data assimilation schemes with empirical background models of the ionosphere are already in operational use. However such methods suffer during disturbed conditions when large gradients are present and are moving relatively fast through the modeled domain. Also, such schemes have limited forecasting capabilities. In order to improve disturbed conditions modeling, more sophisticated assimilation schemes based on sparse measurements for the coupled thermosphere ionosphere system are needed. We have implemented an ensemble Kalman Filter (enKF) for the Thermosphere-Ionosphere (TI) system. We used the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) model as the background for an assimilation scheme and created the Thermosphere Ionosphere Data Assimilation (TIDA) software package. We published our first paper discussing neutral mass density assimilation during quiet geomagnetic conditions in Space Weather in 2018. In this paper we present results from experiments during the 2003 Halloween Storm, 27-31 October 2003, under very disturbed (K$_p$ = 9) conditions while assimilating GRACE-A and B, and CHAMP neutral density measurements. TIDA was able to simulate this disturbed period without using the L1 solar wind measurements which were contaminated by solar energetic protons, by estimating the model inputs from the density measurements. TIDA is being prepared to offer specification and short term forecasts of neutral density for satellite drag and debris collision avoidance for space traffic management. We also plan to offer long term (solar cycle length), average neutral density estimation for satellite fleet management.