A comparison of the effects of initializing different thermosphere‐ionosphere model fields on storm time plasma density forecasts

Abstract

[1] Data assimilation has been used successfully for real-time ionospheric specification, but it has not yet proved advantageous for forecasting. The most challenging and important ionospheric events to forecast are storms. The work presented here examines the effectiveness of data assimilation in a storm situation, where the initial conditions are known and the model is considered to be correct but the external solar and geomagnetic drivers are poorly specified. The aim is to determine whether data assimilation could be used to improve storm time forecast accuracy. The results show that, in the case of the storm of Halloween 2003, changes made to the model's initial thermospheric conditions improve electron density forecasts by at least 10% for 18 h, while changes to ionospheric fields alone result in >10% forecast accuracy improvement for less than 4 h. Further examination shows that the neutral composition is especially important to the accuracy of ionospheric electron density forecasts. Updating the neutral composition gives almost all the benefits of updating the complete thermospheric state. A comparison with real, globally distributed observations of vertical total electron content confirms that updating the thermospheric composition can improve forecast accuracy.

Scientific challenges in thermosphere-ionosphere forecasting – conclusions from the October 2014 NASA JPL community workshop

“…geomagnetic storms). We note that a recent study by Chartier et al (2013) suggests that even under strong forcing, data assimilation has value in the thermosphere for shorter term forecasts of about 6 h or so.…”

“…As such, this approach explores a ''coarse-grained'' forecast. An even coarser evaluation approach was used by Chartier et al (2013), which analyzed the mean electron density globally from the TIE-GCM. The resolution chosen by Meng et al (2016) is sufficient to distinguish the physics in different physical regimes such as day/night, and low, middle, and high latitudes.…”

Analysis and Hindcast Experiments of the 2009 Sudden Stratospheric Warming in WACCMX+DART

“…Forecasting the ionosphere‐thermosphere beyond a few days therefore requires forecasting the solar/geomagnetic activity and the lower atmosphere variability. This is not to say that initial conditions are unimportant for ionosphere‐thermosphere forecasting; rather, beyond a few hours for the ionosphere and several days for the thermosphere they have minimal impact on forecast skill compared to externally forced variability (Chartier et al, ; Jee et al, ). There is therefore a need for improved forecasting of the solar/geomagnetic and lower atmosphere drivers of ionosphere‐thermosphere variability.…”

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

“…Using synthetically generated observations, Chartier et al . [] and Hsu et al . [] have examined the impact of initializing the thermospheric states on long‐term ionospheric forecasting.…”