The First Comparison Between Swarm-C Accelerometer-Derived Thermospheric Densities and Physical and Empirical Model Estimates

The first systematic comparison between Swarm-C accelerometer-derived thermospheric density and both empirical and physics-based model results using multiple model performance metrics is presented. This comparison is performed at the satellite's high temporal 10-s resolution, which provides a meaningful evaluation of the models' fidelity for orbit prediction and other space weather forecasting applications. The comparison against the physical model is influenced by the specification of the lower atmospheric forcing, the high-latitude ionospheric plasma convection, and solar activity. Some insights into the model response to thermosphere-driving mechanisms are obtained through a machine learning exercise. The results of this analysis show that the short-timescale variations observed by Swarm-C during periods of high solar and geomagnetic activity were better captured by the physics-based model than the empirical models. It is concluded that Swarm-C data agree well with the climatologies inherent within the models and are, therefore, a useful data set for further model validation and scientific research.Comment: https://goo.gl/n4QvU

Modelling the descent of nitric oxide during the elevated stratopause event of January 2013

Using simulations with a whole-atmosphere chemistry-climate model nudged by meteorological analyses, global satellite observations of nitrogen oxide (NO) and water vapour by the Sub-Millimetre Radiometer instrument (SMR), of temperature by the Microwave Limb Sounder (MLS), as well as local radar observations, this study examines the recent major stratospheric sudden warming accompanied by an elevated stratopause event (ESE) that occurred in January 2013. We examine dynamical processes during the ESE, including the role of planetary wave, gravity wave and tidal forcing on the initiation of the descent in the mesosphere-lower thermosphere (MLT) and its continuation throughout the mesosphere and stratosphere, as well as the impact of model eddy diffusion. We analyse the transport of NO and find the model underestimates the large descent of NO compared to SMR observations. We demonstrate that the discrepancy arises abruptly in the MLT region at a time when the resolved wave forcing and the planetary wave activity increase, just before the elevated stratopause reforms. The discrepancy persists despite doubling the model eddy diffusion. While the simulations reproduce an enhancement of the semi-diurnal tide following the onset of the 2013 SSW, corroborating new meteor radar observations at high northern latitudes over Trondheim (63.4$^{\circ}$N), the modelled tidal contribution to the forcing of the mean meridional circulation and to the descent is a small portion of the resolved wave forcing, and lags it by about ten days

Validation of Ionospheric Specifications During Geomagnetic Storms: TEC and foF2 During the 2013 March Storm Event

To address challenges of assessing space weather modeling capabilities, the CommunityCoordinated Modeling Center is leading a newly establishedInternational Forum for Space WeatherModeling Capabilities Assessment. This paper presents preliminary results of validation of modeled foF2 (F2 layer critical frequency) and TEC (total electron content) during the first selected 2013 March storm event (17 March 2013). In this study, we used eight ionospheric models ranging from empirical to physics-based, coupled ionosphere-thermosphere and data assimilation models. The quantities we considered are TEC and foF2 changes and percentage changes compared to quiet time background, and the maximum and minimum percentage changes. In addition, we considered normalized percentage changes of TEC. We compared the modeled quantities with ground-based observations of vertical Global Navigation SatelliteSystem TEC (provided by Massachusetts Institute of Technology Haystack Observatory) and foF2 data (provided by Global Ionospheric Radio Observatory) at the 12 locations selected in middle latitudes of the American and European-African longitude sectors. To quantitatively evaluate the models’ performance, we calculated skill scores including correlation coefficient, root-mean square error (RMSE), ratio of the modeled to observed maximum percentage changes (yield), and timing error. Our study indicates that average RMSEs of foF2range from about 1 MHz to 1.5 MHz. The average RMSEs of TEC are between ~5 and ~10 TECU (1 TEC Unit= 1016el/m2). dfoF2[%] RMSEs are between 15% and 25%, which is smaller than RMSE of dTEC[%] ranging from30% to 60%. The performance of the models varies with the location and metrics considered

Using the local ensemble transform Kalman filter for upper atmospheric modelling

The Advanced Ensemble electron density (Ne) Assimilation System (AENeAS) is a new data assimilation model of the ionosphere/thermosphere. The background model is provided by the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIE-GCM) and the assimilation uses the local ensemble transform Kalman filter (LETKF). An outline derivation of the LETKF is provided and the equations are presented in a form analogous to the classic Kalman filter. An enhancement to the efficient LETKF implementation to reduce computational cost is also described. In a 3 day test in June 2017, AENeAS exhibits a total electron content (TEC) RMS error of 2.1 TECU compared with 5.5 TECU for NeQuick and 6.8 for TIE-GCM (with an NeQuick topside)

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

This paper assimilates the in-situ O+ fluxes observations obtained from the Advanced Ionospheric Probe (AIP) onboard the upcoming FORMOSAT-5 (FS-5) satellite and evaluates its possible impact on the ionospheric space weather forecast model. The Observing System Simulation Experiment (OSSE), designed for the global O+ fluxes, is shown to improve the electron density specification in the vicinity of satellite orbits. The root-mean-square-error (RMSE) of the ionospheric electron density obtained from assimilating the daytime O+ fluxes could be improved by ~10 and ~5% for the forecast and nowcast, respectively. Although the improvement of nighttime O+ flux assimilation is less significant compared to the daytime assimilation, it still reveals impacts on the model result. This suggests that nighttime observations might not be sufficient to alter the model trajectory in the positive direction as with the daytime result. Alternative data assimilation approaches, such as assimilation of the empirical model built by using the nighttime FS-5/AIP together with other existing satellite observations of O+ flux could obtain better accuracy of the electron density forecast

Retrospective Cost Optimization for Adaptive State Estimation, Input Estimation, and Model Refinement

AbstractRetrospective cost optimization was originally developed for adaptive control. In this paper, we show how this technique is applicable to three distinct but related problems, namely, state estimation, input estimation, and model refinement. To illustrate these techniques, we give two examples. In the first example, retrospective cost model refinement is used with synthetic data to estimate the cooling dynamics that are missing from a model of the ionosphere-thermosphere. In the second example, retrospective cost adaptive state estimation is used with data from a satellite to estimate a solar driver in the ionosphere- thermosphere, with performance gauged by using data from a second satellite