Thermospheric Mass Density Variations Research Articles

Improving the Extraction Ability of Thermospheric Mass Density Variations From Observational Data by Deep Learning

AbstractUnderstanding the variation of the Thermospheric Mass Density (TMD) is important for solar‐terrestrial physics and applications for spacecraft safety. The thermosphere, as an open system, is impacted by various space environment conditions and has complicated temporal and spatial features. Consequently, TMD observations contain a wealth of multi‐scale feature information. How to extract such information from observations is a challenge that requires ongoing research. It is vital to improving our understanding of the TMD features. Deep learning (DL) can learn complex representations directly from raw data, which makes it a compelling feature extraction and modeling tool for providing a novel perspective for TMD modeling. The Residual Network is used in this study to build a DL model with deep network architecture. The observations of CHAllenging Minisatellite Payload are utilized in the training phase, while the Gravity Recovery and Climate Experiment, High Accuracy Satellite Drag Model and Naval Research Laboratory Mass Spectrometer and Incoherent Scatter radar Extended model are used to evaluate the performance of the DL model. The results reveal that, compared with the shallow model of the typical Multi‐Layer Perceptron, the DL model can better extract multi‐scale features in the observations while retaining generalization capabilities. Controlled simulation experiments allow us to extract the effects of different physical processes, which improves the interpretability of the DL model. It is demonstrated that the DL model can discriminate the physical processes corresponding to the different space environment indices by simulating Equatorial Mass density Anomaly and geomagnetic storms.

Distinct thermospheric mass density variations following the September 2017 geomagnetic storm from GRACE and Swarm

Geomorphologies and mechanisms of thermospheric mass density variations caused by geomagnetic storms are still challenging due to limited observations and imprecise models. Recently, precise orbit determination (POD) of Gravity Recovery and Climate Experiment (GRACE) and Swarm satellites is able to estimate thermospheric mass density variations, which may provide data to study thermospheric mass density variations following the storm. In this paper, the thermospheric mass density is estimated from GRACE-A and Swarm-A POD and the distinct thermospheric mass density variations are investigated as function of latitude during the September 2017 geomagnetic storm. Different enhancements in mass density response to the geomagnetic storm are presented for the Northern (GRACE) and the Southern (Swarm) Hemispheres. Swarm observations show symmetric mass density variations between two hemispheres and a slightly stronger enhancement in Southern Hemisphere. GRACE POD and accelerometer observations both show a very strong enhancement in Northern Hemisphere while no corresponding enhancement in Southern Hemisphere. This anomaly may attribute to the effects of vertical winds in high latitude region and plasma drift considering the similar solar zenith angles in both hemispheres.

Thermospheric density estimation and responses to the March 2013 geomagnetic storm from GRACE GPS-determined precise orbits

The thermospheric mass density variations and the thermosphere-ionosphere coupling during geomagnetic storms are not clear due to lack of observables and large uncertainty in the models. Although accelerometers on-board Low-Orbit-Earth (LEO) satellites can measure non-gravitational accelerations and derive thermospheric mass density variations with unprecedented details, their measurements are not always available (e.g., for the March 2013 geomagnetic storm). In order to cover accelerometer data gaps of Gravity Recovery and Climate Experiment (GRACE), we estimate thermospheric mass densities from numerical derivation of GRACE determined precise orbit ephemeris (POE) for the period 2011–2016. Our results show good correlation with accelerometer-based mass densities, and a better estimation than the NRLMSISE00 empirical model. Furthermore, we statistically analyze the differences to accelerometer-based densities, and study the March 2013 geomagnetic storm response. The thermospheric density enhancements at the polar regions on 17 March 2013 are clearly represented by POE-based measurements. Although our results show density variations better correlate with Dst and k-derived geomagnetic indices, the auroral electroject activity index AE as well as the merging electric field Em picture better agreement at high latitude for the March 2013 geomagnetic storm. On the other side, low-latitude variations are better represented with the Dst index. With the increasing resolution and accuracy of Precise Orbit Determination (POD) products and LEO satellites, the straightforward technique of determining non-gravitational accelerations and thermospheric mass densities through numerical differentiation of POE promises potentially good applications for the upper atmosphere research community.

New modes and mechanisms of thermospheric mass density variations from GRACE accelerometers

AbstractMonitoring and understanding the upper atmosphere processes is important for orbital decay and space physics. Nowadays, Low Earth Orbit (LEO) accelerometers provide a unique opportunity to study thermospheric density variations with unprecedented details. In this paper, thermospheric mass densities variations from Gravity Recovery and Climate Experiment (GRACE) accelerometers are investigated for the period 2003–2016 using the principal component analysis (PCA). The resulting modes are analyzed and parameterized in terms of solar and magnetospheric forcing, local solar time (LST), and annual variations. A better understanding of global thermospheric air density variations is presented, which validates the suitability of our technique and model. The parameterization of the subsolar‐point annual variation shows two maxima around June and only one in December. The LST parameterization shows a new fluctuation controlling a middle latitude four‐wave pattern, with two maxima at 12 h and 21 h LST and two minima at 1 h and 17 h LST. Our parameterizations are suitable to represent small‐scale variations including, e.g., the equatorial mass density anomaly (EMA) and the midnight density maximum (MDM). Finally, the residuals are analyzed in the spectral domain, and additional contributions are found at the frequencies of the radiational tides and at the periods of 83, 93, 152, and 431 days.

Pathways of F region thermospheric mass density enhancement via soft electron precipitation

AbstractThe efficiencies of pathways of thermospheric heating via soft electron precipitation in the dayside cusp region are investigated using the coupled magnetosphere‐ionosphere‐thermosphere model (CMIT). Event‐based data‐model comparisons show that the CMIT model is capable of reproducing the thermospheric mass density variations measured by the CHAMP satellite during both quite and active periods. During the 24 August 2005 storm event (Kp = 6−) while intense Joule heating rate occurs in the polar cusp region, including soft electron precipitation is important for accurately modeling the F region thermospheric mass density distribution near the cusp region. During the 27 July 2007 event (Kp = 2−) while little Joule heating rate occurs in the polar cusp region, the controlled CMIT simulations suggest that the direct pathway through the energy exchange between soft electrons and thermospheric neutrals is the dominant process during this event, which only has a small effect on the neutral temperature and mass density at 400 km altitude. Comparisons between the two case studies show that the indirect pathway via increasing the F region Joule heating rate is a dominant process during the 24 August 2005 storm event, which is much more efficient than the direct heating process.

Predicting storm-time thermospheric mass density variations at CHAMP and GRACE altitudes

Abstract. Orbit-averaged mass density measurements derived from the satellites CHAMP and GRACE are used to investigate the storm-time prediction model developed by Liu et al. (2010) at different altitudes. This model uses as input only the solar wind merging electric field. From 2002 to 2005 in total 31 major geomagnetic storms with minimum Dst

Thermospheric mass density variations during geomagnetic storms and a prediction model based on the merging electric field

Abstract. With the help of four years (2002–2005) of CHAMP accelerometer data we have investigated the dependence of low and mid latitude thermospheric density on the merging electric field, Em, during major magnetic storms. Altogether 30 intensive storm events (Dstmin<−100 nT) are chosen for a statistical study. In order to achieve a good correlation Em is preconditioned. Contrary to general opinion, Em has to be applied without saturation effect in order to obtain good results for magnetic storms of all activity levels. The memory effect of the thermosphere is accounted for by a weighted integration of Em over the past 3 h. In addition, a lag time of the mass density response to solar wind input of 0 to 4.5 h depending on latitude and local time is considered. A linear model using the preconditioned Em as main controlling parameter for predicting mass density changes during magnetic storms is developed: ρ=0.5 Em + ρamb, where ρamb is based on the mean density during the quiet day before the storm. We show that this simple relation predicts all storm-induced mass density variations at CHAMP altitude fairly well especially if orbital averages are considered.

Periodic modulations in thermospheric composition by solar wind high speed streams

ΣO/N2 ratios in the Earth's thermosphere are measured by the Global Ultraviolet Imager (GUVI) on the TIMED satellite, and demonstrate strong 9 and 7 day oscillations in 2005 and 2006, respectively, that are well correlated with the solar wind speed and Kp index. This work builds on the recently discovered connection between rotating solar coronal holes and thermospheric mass density variations. The work described here is the first description of geomagnetically forced periodicities in neutral composition. Furthermore, these observations provide the first definitive proof that the processes creating neutral composition changes during geomagnetic storms occur continuously at all activity levels and all over the world. The ΣO/N2 response versus the mass density response indicates the important role of vertical winds at high latitudes while thermal expansion dominates at lower latitudes.