Statistical Approach to Observe the Atmospheric Density Variations Using Swarm Satellite Data

• Main Authors: Md Wahiduzzaman, Alea Yeasmin, Jing-Jia Luo, Md. Arfan Ali, Muhammad Bilal, Zhongfeng Qiu
• Format: Article
• Language: English
• Published: MDPI AG 2020-08-01
• Series: Atmosphere
• Subjects: atmospheric density; temporal variation; Swarm mission; correlation coefficients; solar and geomagnetic indices
• Online Access: https://www.mdpi.com/2073-4433/11/9/897

Over time, the initial algorithms to derive atmospheric density from accelerometers have been significantly enhanced. In this study, we discussed one of the accurate accelerometers—the Earth’s Magnetic Field and Environment Explorers, more commonly known as the Swarm satellites. Swarm satellite–C level 2 (measurements from the Swam accelerometers) density, solar index (F_10.7), and geomagnetic index (Kp) data have been used for a year (mid 2014–2015), and the different types of temporal (the diurnal, multi–day, solar–rotational, semi–annual, and annual) atmospheric density variations have been investigated using the statistical approaches of correlation coefficient and wavelet transform. The result shows the density varies due to the recurrent geomagnetic force at multi–day, solar irradiance during the day, appearance and disappearance of the Sun’s active region, Sun–Earth distance, large scale circulation, and the formation of an aurora. Additionally, a correlation coefficient was used to observe whether F_10.7 or Kp contributes strongly or weakly to annual density, and the result found a strong (medium) correlation with F_10.7 (Kp). Accurate density measurement can help to reduce the model’s bias correction, and monitoring the physical mechanisms for the density variations can lead to improvements in the atmospheric density models.