The Effect of Atmospheric Drag Force on the Elements of Low Earth Orbital Satellites at Minimum Solar Activity

Researching and modeling perturbations is essential in astrodynamics because it gives information on the deviations from the satellite's normal, idealized, or unperturbed motion. Examined the impact of non-conservative atmospheric drag and orbital elements of low-earth-orbit satellites under low solar activity. The study is consisting of parts, the first looks at the effects of atmospheric drag on LEO satellites different area to mass ratios, and the second looks at different inclination values. Modeling the impacts of perturbation is included in each section, and the final portion determines the effects of atmospheric drag at various node values. The simulation was run using the Celestial Mechanics software system's SATORB module (Beutler, 2005), which solves the perturbation equations via numerical integration. The findings were examined using Matlab 2012. Conclusion that the impacts are stronger for retrograde orbits, which is due to the fact that the satellite moves in the opposite direction. The atmospheric drag effects for all orbital elements were increased by increasing the area to mass ratio. When the node value rises, the size parameter changes slightly, but the other orbital elements change. At varying inclinations, it is found that the changes in orbital elements due to atmospheric drug.

Spatio-temporal development of large scale auroral electrojet currents relative to substorm onsets

During auroral substorms the electric currents flowing in the ionosphere change rapidly and a large amount of energy is dissipated in the auroral ionosphere. An important part of the auroral current system are the auroral electrojets whose profiles can be estimated from magnetic field measurements from Low Earth Orbit satellites. In this paper we combine electrojet data derived from the Swarm satellite mission of ESA with the substorm database derived from the SuperMAG ground magnetometer network data. We organize the electrojet data in relation to the location and time of the onset and obtain statistics for the development of the integrated current and latitudinal location for the auroral electrojets relative to the onset. The major features of the behaviour of the westward electrojet are found to be in accordance with earlier studies of field aligned currents and ground magnetometer observations of substorm time statistics. In addition we show that after the onset the latitudinal location of the maximum of the westward electrojet determined from Swarm satellite data is mostly located close to the SuperMAG onset latitude in the local time sector of the onset regardless of where the onset happens. We also show that the SuperMAG onset corresponds to a strengthening of the order of 100 kA in the amplitude of the median of the westward integrated current in the Swarm data from 15 minutes before to 15 minutes after the onset.

Integration of GOCI and AHI Yonsei aerosol optical depth products during the 2016 KORUS-AQ and 2018 EMeRGe campaigns

The Yonsei Aerosol Retrieval (YAER) algorithm for the Geostationary Ocean Color Imager (GOCI) retrieves aerosol optical properties only over dark surfaces, so it is important to mask pixels with bright surfaces. The Advanced Himawari Imager (AHI) is equipped with three shortwave-infrared and nine infrared channels, which is advantageous for bright-pixel masking. In addition, multiple visible and near-infrared channels provide a great advantage in aerosol property retrieval from the AHI and GOCI. By applying the YAER algorithm to 10 min AHI or 1 h GOCI data at 6 km×6 km resolution, diurnal variations and aerosol transport can be observed, which has not previously been possible from low-Earth-orbit satellites. This study attempted to estimate the optimal aerosol optical depth (AOD) for East Asia by data fusion, taking into account satellite retrieval uncertainty. The data fusion involved two steps: (1) analysis of error characteristics of each retrieved result with respect to the ground-based Aerosol Robotic Network (AERONET), as well as bias correction based on normalized difference vegetation indexes, and (2) compilation of the fused product using ensemble-mean and maximum-likelihood estimation (MLE) methods. Fused results show a better statistics in terms of fraction within the expected error, correlation coefficient, root-mean-square error (RMSE), and median bias error than the retrieved result for each product. If the RMSE and mean AOD bias values used for MLE fusion are correct, the MLE fused products show better accuracy, but the ensemble-mean products can still be useful as MLE.