Impact of small- and meso-scale electromagnetic field variability on the high-latitude energy input - Jinlong Ji; Jinlong Ji; Yanshi Huang (Frontiers in Physics)
In this study, the high-resolution data from the Defense Meteorological Satellite Program (DMSP) satellites are used to investigate the contribution and impact of small- and meso-scale electromagnetic field variability with different scales on the estimation of Joule heating and Poynting flux. Smoothing windows with various sizes, such as 5°, 2.5°, 1° magnetic latitude, are used to analyze the characteristics of electromagnetic field variability during the March 2015 geomagnetic storm event. The results show that the small- and meso-scale filed variability can either increase or decrease the estimation of the total Joule heating and Poynting flux during the storm main phase by more than 100% with a smoothing window size of 5° latitude. During the whole period of this storm event, the electric field variability with scales smaller than 5° latitude accounts for 47% of the total electric field on average, whereas the magnetic field variability with scales smaller than 5° latitude only takes 10% of the total magnetic field. Moreover, the mean magnitude changes of Joule heating and Poynting flux due to small- and meso-scale electromagnetic field variability are 58% and 52%, respectively. The impact of small- and meso-scale field variabilities on the energy estimation decreases when smaller smoothing windows are applied, for example, with a size of 0.1° latitude window, the mean magnitude changes of Joule heating and Poynting flux are 20% and 17%, respectively. This demonstrates that finer grids can capture more contribution of small- and meso-scale variabilities in the calculation of Joule heating and Poynting flux. It is very important to use high-resolution grids to calculate the total energy input at high latitudes during storm events. These results will help improve the estimation of high-latitude energy input in the general circulation models, thereby more accurately predict the changes in upper atmospheric parameters.