Ionospheric data assimilation and forecasting during storms

Abstract

Ionospheric storms can have important effects on radio communications and navigation systems.Storm time ionospheric predictions have the potential to form part of effective mitigation strategies to these problems. Ionospheric storms are caused by strong forcing from the solar wind. Electron density enhancements are driven by penetration electric fields, as well as by thermosphere-ionosphere behavior including Traveling Atmospheric Disturbances and Traveling Ionospheric Disturbances and changes to the neutral composition. This study assesses the effect on 1 h predictions of specifying initial ionospheric and thermospheric conditions using total electron content (TEC) observations under a fixed set of solar and high-latitude drivers. Prediction performance is assessed against TEC observations, incoherent scatter radar, and in situ electron density observations. Corotated TEC data provide a benchmark of forecast accuracy. The primary case study is the storm of 10 September 2005, while the anomalous storm of 21 January 2005 provides a secondary comparison. The study uses an ensemble Kalman filter constructed with the Data Assimilation Research Testbed and the Thermosphere Ionosphere Electrodynamics General Circulation Model. Maps of preprocessed, verticalized GPS TEC are assimilated, while high-latitude specifications from the Assimilative Mapping of Ionospheric Electrodynamics and solar flux observations from the Solar Extreme Ultraviolet Experiment are used to drive the model. The filter adjusts ionospheric and thermospheric parameters, making use of time-evolving covariance estimates. The approach is effective in correcting model biases but does not capture all the behavior of the storms. In particular, a ridge-like enhancement over the continental USA is not predicted, indicating the importance of predicting storm time electric field behavior to the problem of ionospheric forecasting.

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

“…Chartier et al . [] assimilated the ground‐based TEC observations into a coupled thermosphere‐ionosphere model during a major storm of Kp 7–8 and evaluated their model capabilities/performances for storm time short‐term forecasting. Using synthetically generated observations, Chartier et al .…”

EnKF Ionosphere and Thermosphere Data Assimilation Algorithm Through a Sparse Matrix Method

“…Hsu et al (2018) did several observing system simulation experiments (OSSEs) based on the Ensemble Square Root Filter (EnSRF) for COSMIC-2 observations and concluded that the assimilation of slant TEC data from COSMIC-2 can considerably improve the global ionospheric specification and prediction. However, in these above studies, the authors usually applied the commonly used software packages to implement EnKF/EnSRF, including the Gridpoint Statistical Interpolation (Hsu et al, 2018;Wu et al, 2002) and the Data Assimilation Research Testbed (Anderson et al, 2009;Chartier et al, 2016;Chen et al, 2017;Lee et al, 2012;Matsuo et al, 2013;Pedatella et al, 2018), which rely on large-scale parallel high-performance computing systems. However, in these above studies, the authors usually applied the commonly used software packages to implement EnKF/EnSRF, including the Gridpoint Statistical Interpolation (Hsu et al, 2018;Wu et al, 2002) and the Data Assimilation Research Testbed (Anderson et al, 2009;Chartier et al, 2016;Chen et al, 2017;Lee et al, 2012;Matsuo et al, 2013;Pedatella et al, 2018), which rely on large-scale parallel high-performance computing systems.…”

“…However, the majority of previous studies were conducted on supercomputers, such as NCAR Yellowstone (Chartier et al, 2016;Hsu et al, 2014;Lee et al, 2012;Matsuo et al, 2013) or Cheyenne supercomputer (Pedatella et al, 2018). However, the majority of previous studies were conducted on supercomputers, such as NCAR Yellowstone (Chartier et al, 2016;Hsu et al, 2014;Lee et al, 2012;Matsuo et al, 2013) or Cheyenne supercomputer (Pedatella et al, 2018).…”

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

“…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.…”