Thermospheric Neutral Density Research Articles

Assimilating Space‐Based Thermospheric Neutral Density (TND) Data Into the TIE‐GCM Coupled Model During Periods With Low and High Solar Activity

AbstractThe global estimation of Thermospheric Neutral Density (TND) and electron density (Ne) on various altitudes are provided by upper atmosphere models, however, the quality of their forecasts needs to be improved. In this study, we present the impact of assimilating space‐based TNDs, measured along Low Earth Orbit (LEO) mission, into the NCAR Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model (TIE‐GCM). In these experiments, the Ensemble Kalman Filter (EnKF) merger of the Data Assimilation Research Testbed (DART) community software is applied. To cover various space‐based TND data and both low and high solar activity periods, we used the measurements of CHAMP (Challenging Minisatellite Payload) and Swarm‐C as assimilated observations. The TND forecasts are then validated against independent TNDs of GRACE (Gravity Recovery and Climate Experiment mission) and Swarm‐B, respectively. To introduce the impact of the thermosphere on estimating ionospheric parameters, the outputs of Ne are validated against the radio occultation data. The Data Assimilation (DA) results indicate that TIE‐GCM overestimates (underestimates) TND and Ne during low (high) solar activity. Considerable improvements are found in forecasting TNDs after DA, that is, the Root Mean Squared Error (RMSE) is reduced by 79% and 51% during low and high solar activity periods, respectively. The reduction values for Ne are found to be 52.3% and 40.4%, respectively.

Predicting global thermospheric neutral density during periods with high geomagnetic activity

Estimating global and multi-level Thermosphere Neutral Density (TND) is important for studying coupling processes within the upper atmosphere, and for applications like orbit prediction. Models are applied for predicting TND changes, however, their performance can be improved by accounting for the simplicity of model structure and the sampling limitations of model inputs. In this study, a simultaneous Calibration and Data Assimilation (C/DA) algorithm is applied to integrate freely available CHAMP, GRACE, and Swarm derived TND measurements into the NRLMSISE-00 model. The improved model, called ‘C/DA-NRLMSISE-00’, and its outputs fit to these measured TNDs, are used to produce global TND fields at arbitrary altitudes (with the same vertical coverage as the NRLMSISE-00). Seven periods, between 2003-2020 that are associated with relatively high geomagnetic activity selected to investigate these fields, within which available models represent difficulties to provide reasonable TND estimates. Independent validations are performed with along-track TNDs that were not used within the C/DA framework, as well as with the outputs of other models such as the Jacchia-Bowman 2008 and the High Accuracy Satellite Drag Model. The numerical results indicate an average 52%, 50%, 56%, 25%, 47%, 54%, and 63% improvement in the Root Mean Squared Errors of the short term TND forecasts of C/DA-NRLMSISE00 compared to the along-track TND estimates of GRACE (2003, altitude 490 km), GRACE (2004, altitude 486 km), CHAMP (2008, altitude 343 km), GOCE (2010, altitude 270 km), Swarm-B (2015, altitude 520 km), Swarm-B (2017, altitude 514 km), and Swarm-B (2020, altitude 512 km), respectively.

Interhemispheric Asymmetry of the Thermospheric Neutral Density Response to the 7–9 September 2017 Geomagnetic Storms

AbstractThe thermospheric neutral density response to the 7–9 September 2017 storms is investigated based on the Swarm satellite observations and the thermosphere‐ionosphere‐electrodynamic general circulation model (TIEGCM) simulation. The Swarm data depicted a prominent interhemispheric asymmetry (IHA) in the afternoon sector during the second storm, a feature that was yet explained. Driven by realistic high‐latitude electric potential and electron precipitation patterns, the TIEGCM is able to reproduce the observed storm‐time neutral density response. The TIEGCM simulation reveals that the differences in the traveling atmospheric disturbances (TADs) is largely responsible for the observed IHA in the neutral mass density response at low and middle latitudes, whereas the difference in mean molecular mass between the two hemispheres may contribute to the IHA in neutral density at higher latitudes. The IHAs in TADs and mean molecular mass are attributed to the IHA in Joule heating dissipation on the night and dawn sides.

Simulated long-term evolution of the thermosphere during the Holocene – Part 1: Neutral density and temperature

Abstract. In the previous work of Yue et al. (2022), the ionospheric evolution during the Holocene (9455 BC to 2015 AD) was comprehensively and carefully investigated for the first time using the Global Coupled Ionosphere-Thermosphere-Electrodynamics Model developed at the Institute of Geology and Geophysics, Chinese Academy of Sciences (GCITEM-IGGCAS), driven by realistic geomagnetic fields, CO2 levels, and solar activity derived from ancient media records and modern measurements. In this study, we further quantify the effects of the three drivers on thermospheric neutral density and temperature variations during the Holocene. We find that the oscillations of solar activity contribute more than 80 % of the thermospheric variability, while either CO2 or the geomagnetic field contributes less than 10 %. The effect of CO2 on the global mean neutral density and temperature is comparable to that of the geomagnetic field throughout the Holocene but is more significant after 1800 AD. In addition, thermospheric density and temperature show approximately linear variations with the dipole moment of the geomagnetic field, CO2, and F10.7, with only the linear growth rate associated with the geomagnetic field varying significantly in universal time and latitude. The increasing dipole moment and CO2 cool and contract the thermosphere, while solar activity has the opposite effect. The higher the altitude, the greater the influence of the three factors on the thermosphere. Different factors produce different seasonal variations in thermosphere changes. Furthermore, we predict that a 400 ppm increase in CO2 will result in a 50 %–70 % and 84–114 K reduction in global mean neutral density and temperature, respectively, which should directly affect the orbit and lifetime of spacecraft and space debris.

Multi‐Model Ensembles for Upper Atmosphere Models

AbstractMulti‐model ensembles (MMEs) are used to improve the forecasts of thermospheric neutral densities. A variety of algorithms for constructing the model weights for the MMEs are described and have been implemented including: performance weighting, independence weighting, and non‐negative least squares. Using both empirical and physics‐based models, compared against in situ Challenging Minisatellite Payload (CHAMP) observations, the skill of each MME weighting approach has been tested in both solar minimum and maximum conditions. In both cases the MME performs better than any individual model. A non‐negative least squares weighting for the MME on a set of bias corrected models provides a 68% and 50% reduction in the mean square error compared to the best model (Jacchia‐Bowman 2008) in the solar minimum and maximum cases, respectively.

Effects of Solar Extreme Ultraviolet Radiation on Thermospheric Neutral Density

对2001－2021年SOHO卫星的极紫外辐射测量数据，以及CHAMP，GRACE-A和SWARM-C卫星资料推导出的高分辨率大气密度数据进行统计分析，发现大气密度与极紫外测量值的相关系数大于密度与<i>F</i>_10.7指数的相关系数，证实极紫外辐射在不同地方时的影响程度存在显著差异，从而驱动大气密度的周日变化。利用三颗卫星的高度差异揭示极紫外辐射对大气密度的加热效应在350～500 km范围随着高度增加而减弱。统计得到极紫外辐射影响在地方时和纬度上的空间差异：对夏季半球的影响大于冬季半球；在白天，对中纬度地区的影响高于赤道和高纬度地区；在夜间，密度对辐射的斜率在夏季半球高纬度地区存在峰值，在冬季半球中纬度存在谷值，模型DTM2000和NRLMSISE00未能准确刻画。为了改进经验模型，提出基于球谐函数的拟合方法，优于主流模型周日效应采用的表达式，对周日效应建模和修正提供有益借鉴。利用昼夜间能量传输和热层大气经向环流机制探讨了统计结果的物理机制。

New thermosphere neutral mass density and crosswind datasets from CHAMP, GRACE, and GRACE-FO

We present new neutral mass density and crosswind observations for the CHAMP, GRACE, and GRACE-FO missions, filling the last gaps in our database of accelerometer-derived thermosphere observations. For consistency, we processed the data over the entire lifetime of these missions, noting that the results for GRACE in 2011–2017 and GRACE-FO are entirely new. All accelerometer data are newly calibrated. We modeled the temperature-induced bias variations for the GRACE accelerometer data to counter the detrimental effects of the accelerometer thermal control deactivation in April 2011. Further, we developed a new radiation pressure model, which uses ray tracing to account for shadowing and multiple reflections and calculates the satellite’s thermal emissions based on the illumination history. The advances in calibration and radiation pressure modeling are essential when the radiation pressure acceleration is significant compared to the aerodynamic one above 450 km altitude during low solar activity, where the GRACE and GRACE-FO satellites spent a considerable fraction of their mission lifetime. The mean of the new density observations changes only marginally, but their standard deviation shows a substantial reduction compared to thermosphere models, up to 15% for GRACE in 2009. The mean and standard deviation of the new GRACE-FO density observations are in good agreement with the GRACE observations. The GRACE and CHAMP crosswind observations agree well with the physics-based TIE-GCM winds, particularly the polar wind patterns. The mean observed crosswind is a few tens of m·s−1larger than the model one, which we attribute primarily to the crosswind errors being positive by the definition of the retrieval algorithm. The correlation between observed and model crosswind is about 60%, except for GRACE in 2004–2011 when the signal was too small to retrieve crosswinds reliably.

Improving the estimation of thermospheric neutral density via two-step assimilation of in situ neutral density into a numerical model

AbstractNeutral thermospheric density is an essential quantity required for precise orbit determination of satellites, collision avoidance of satellites, re-entry prediction of satellites or space debris, and satellite lifetime assessments. Empirical models of the thermosphere fail to provide sufficient estimates of neutral thermospheric density along the orbits of satellites by reason of approximations, assumptions and a limited temporal resolution. At high solar activity these estimates can be off by 70% when comparing to observations at 12-hourly averages. In recent decades, neutral density is regularly observed with satellite accelerometers on board of low Earth orbiting satellites like CHAMP, GOCE, GRACE, GRACE-FO, or Swarm. When assimilating such along-track information into global models of thermosphere–ionosphere dynamics, it has been often observed that only a very local sub-domain of the model grid around the satellite’s position is updated. To extend the impact to the entire model domain we suggest a new two-step approach: we use accelerometer-derived neutral densities from the CHAMP mission in a first step to calibrate an empirical thermosphere density model (NRLMSIS 2.0). In a second step, we assimilate—for the first time—densities predicted for a regular three-dimensional grid into the TIE-GCM (Thermosphere Ionosphere Electrodynamics General Circulation Model). Data assimilation is performed using the Local Error-Subspace Transform Kalman Filter provided by the Parallel Data Assimilation Framework (PDAF). We test the new approach using a 2-week-long period containing the 5 April 2010 Geomagnetic storm. Accelerometer-derived neutral densities from the GRACE mission are used for additional evaluation. We demonstrate that the two-step approach globally improves the simulation of thermospheric density. We could significantly improve the density prediction for CHAMP and GRACE. In fact, the offset between the accelerometer-derived densities and the model prediction is reduced by 45% for CHAMP and 20% for GRACE when applying the two-step approach. The implication is that our approach allows one to much better ’transplant’ the precise CHAMP thermospheric density measurements to satellites flying at a similar altitude. Graphical Abstract

Thermospheric Neutral Density Variation During the “SpaceX” Storm: Implications From Physics‐Based Whole Geospace Modeling

AbstractThe Starlink satellites launched on 3 February 2022 were lost before they fully arrived in their designated orbits. The loss was attributed to two moderate geomagnetic storms that occurred consecutively on 3–4 February. We investigate the thermospheric neutral mass density variation during these storms with the Multiscale Atmosphere‐Geospace Environment (MAGE) model, a first‐principles, fully coupled geospace model. Simulated neutral density enhancements are validated by Swarm satellite measurements at the altitude of 400–500 km. Comparison with standalone TIEGCM and empirical NRLMSIS 2.0 and DTM‐2013 models suggests better performance by MAGE in predicting the maximum density enhancement and resolving the gradual recovery process. Along the Starlink satellite orbit in the middle thermosphere (∼200 km altitude), MAGE predicts up to 150% density enhancement near the second storm peak while standalone TIEGCM, NRLMSIS 2.0, and DTM‐2013 suggest only ∼50% increase. MAGE also suggests altitudinal, longitudinal, and latitudinal variability of storm‐time percentage density enhancement due to height dependent Joule heating deposition per unit mass, thermospheric circulation changes, and traveling atmospheric disturbances. This study demonstrates that a moderate storm can cause substantial density enhancement in the middle thermosphere. Thermospheric mass density strongly depends on the strength, timing, and location of high‐latitude energy input, which cannot be fully reproduced with empirical models. A physics‐based, fully coupled geospace model that can accurately resolve the high‐latitude energy input and its variability is critical to modeling the dynamic response of thermospheric neutral density during storm time.

Seasonal Oscillations of Thermosphere Neutral Density at Dusk/Dawn as Measured by Three Satellite Missions

AbstractBased on the neutral mass density measurements from the on‐board accelerometer of Gravity field and steady‐state Ocean Circulation Explorer (GOCE) satellite, the space‐borne atmospheric density detectors on the Atmospheric density detection and Precise Orbit Determination (APOD) satellite and another Chinese satellite (CHN‐sat) over almost a solar cycle, this paper presents the annual and semiannual variations of the dawn/dusk thermosphere mass density at 260 km, 460 km, and 630 km altitudes. Density maxima at dawn appear in the local summer at the southern high latitudes, and near equinoxes in the northern poles with the density maximum in March higher than that in October at solar minimum. Neutral density maxima near 630 km at dusk occur at high latitudes under low solar flux condition, and at low latitudes near the equator at medium solar activity. The latitude‐seasonal density structure obtained from both the CHN‐sat and APOD observations shows a distinct hemisphere asymmetry with a larger magnitude at high latitudes in the summer hemisphere at solar minimum. The semiannual variation dominates from low‐middle latitudes at 260 km altitude and decreases with the increase of solar activity, while the annual variations dominate at 460 and 630 km altitudes in solar minimum. The growth of mass densities with increasing solar radiation gradually saturates in June. The amplitude of annual variation in mass densities at middle‐high latitudes in the Northern Hemisphere (NH) decreases with increasing solar radiation.

Impact of Soft Electron Precipitation on the Thermospheric Neutral Mass Density During Geomagnetic Storms: GITM Simulations

AbstractIn this study, the impact of improving soft (0.1–1 keV) electron precipitation on the F‐region neutral mass density has been evaluated using the Global Ionosphere Thermosphere Model (GITM). Two types of electron energy spectra having the same total energy flux and average energy but different spectral shapes have been used to specify the electron precipitation in GITM. One is the Maxwellian spectrum and the other is from an empirical model, Auroral Spectrum and High‐Latitude Electric field variabilitY (ASHLEY), which provides stronger (up to 2–3 orders of magnitude) soft electron precipitations than the Maxwellian spectrum. Data‐model comparisons indicate that the storm‐time orbital averaged neutral density can be increased by 10%–40% and is more consistent with the observation if the non‐Maxwellian ASHLEY spectrum is used. This study reveals the importance of accurate soft electron precipitation specifications in the whole auroral zone to improving the F‐region neutral mass density estimations.

The North–South Asymmetry of Martian Ionosphere and Thermosphere

AbstractBased on Mars Atmospheric and Volatile EvolutioN's neutral composition and Langmuir probe electron density and temperature data, we statistically analyzed the climatic variations of the Martian thermosphere and ionosphere and found significant north–south asymmetry. In winter and summer, the asymmetry mainly originates from the north–south asymmetry of the solar zenith angle. However, the observed data still exhibit significant north–south asymmetry in equinox seasons. Under low solar extreme ultraviolet radiation, the thermospheric neutral density in the northern hemisphere is higher than that in the southern hemisphere. As solar radiation increases, the neutral density in the southern hemisphere gradually exceeds that in the northern hemisphere. In addition, the southern hemisphere density increases nonlinearly with the increase of solar radiation, whereas the northern hemisphere density increases linearly. The electron density and electron temperature in the Martian ionosphere also exhibit similar north–south asymmetry. The asymmetries in the ionosphere and thermosphere between the northern and southern hemispheres are likely related to significant differences in Mars' north–south topography or to north–south asymmetries in the residual magnetic field. After preliminary analysis, we found that the north–south asymmetry of Mars' remaining magnetic field would intensify the hemispheric asymmetry of the ionospheric electron density, but have no effect on the thermospheric neutral density. The hemispheric asymmetry may be primarily related to the significant difference in Mars' north–south topography.

Uncertainty quantification techniques for data-driven space weather modeling: thermospheric density application

Machine learning (ML) has been applied to space weather problems with increasing frequency in recent years, driven by an influx of in-situ measurements and a desire to improve modeling and forecasting capabilities throughout the field. Space weather originates from solar perturbations and is comprised of the resulting complex variations they cause within the numerous systems between the Sun and Earth. These systems are often tightly coupled and not well understood. This creates a need for skillful models with knowledge about the confidence of their predictions. One example of such a dynamical system highly impacted by space weather is the thermosphere, the neutral region of Earth’s upper atmosphere. Our inability to forecast it has severe repercussions in the context of satellite drag and computation of probability of collision between two space objects in low Earth orbit (LEO) for decision making in space operations. Even with (assumed) perfect forecast of model drivers, our incomplete knowledge of the system results in often inaccurate thermospheric neutral mass density predictions. Continuing efforts are being made to improve model accuracy, but density models rarely provide estimates of confidence in predictions. In this work, we propose two techniques to develop nonlinear ML regression models to predict thermospheric density while providing robust and reliable uncertainty estimates: Monte Carlo (MC) dropout and direct prediction of the probability distribution, both using the negative logarithm of predictive density (NLPD) loss function. We show the performance capabilities for models trained on both local and global datasets. We show that the NLPD loss provides similar results for both techniques but the direct probability distribution prediction method has a much lower computational cost. For the global model regressed on the Space Environment Technologies High Accuracy Satellite Drag Model (HASDM) density database, we achieve errors of approximately 11% on independent test data with well-calibrated uncertainty estimates. Using an in-situ CHAllenging Minisatellite Payload (CHAMP) density dataset, models developed using both techniques provide test error on the order of 13%. The CHAMP models—on validation and test data—are within 2% of perfect calibration for the twenty prediction intervals tested. We show that this model can also be used to obtain global density predictions with uncertainties at a given epoch.

Influence of the solar wind high-speed streams on the thermospheric neutral density during the declining phase of solar cycle 23

Thermospheric neutral density derived from the GRACE A satellite and normalized at altitude of 490 km (ρ) are used to investigate the ρ behavior during the period of recurrent geomagnetic activity (25 January - 5 May, 2005) caused by solar wind high-speed streams (HSSs). The north and south hemispheric ρ values divided in three latitudinal bins are analyzed separately at dayside and nightside. The variations, not caused by solar/geomagnetic activity, are investigated accounting for the relationship between solar flux index, illumination, latitude and DOY for particular magnetic local times (MLTs). Analysis has shown that: ρ increases/decreases from high to low latitudes at dayside/nightside; ρ increases from high to low latitudes at dayside caused by solar EUV radiation is most prominent around MLT = 14 and decrease rapidly with departure from this MLT; the difference between north and south hemispheric ρ values are not the same prior and after the equinox; quiet time ρ differs among latitudinal bins; ρ contains a clear imprint of solar/geomagnetic activity. The cross-correlation analysis reveals a high degree of correlation between ρ and different employed ρ indicators. Time lags based on all ρ indicators suggest that ρ disturbance: occurs about 4 h earlier at high than at lower latitudes and propagates presumably without losses toward equatorial region both at dayside and nightside; propagates faster between polar and mid latitudes at dayside and between mid and low latitudes at nightside. This study provides the most probable characteristics of the ρ variations during the periods in which magnetospheric-thermospheric system is affected primarily by HSSs.

Machine‐Learned HASDM Thermospheric Mass Density Model With Uncertainty Quantification

AbstractA thermospheric neutral mass density model with robust and reliable uncertainty estimates is developed based on the Space Environment Technologies (SET) High Accuracy Satellite Drag Model (HASDM) density database. This database, created by SET, contains 20 years of outputs from the U.S. Space Force's HASDM, which currently represents the state of the art for density and drag modeling. We utilize principal component analysis for dimensionality reduction, which creates the coefficients upon which nonlinear machine‐learned (ML) regression models are trained. These models use three unique loss functions: Mean square error (MSE), negative logarithm of predictive density (NLPD), and continuous ranked probability score. Three input sets are also tested, showing improved performance when introducing time histories for geomagnetic indices. These models leverage Monte Carlo dropout to provide uncertainty estimates, and the use of the NLPD loss function results in well‐calibrated uncertainty estimates while only increasing error by 0.25% (&lt;10% mean absolute error) relative to MSE. By comparing the best HASDM‐ML model to the HASDM database along satellite orbits, we found that the model provides robust and reliable density uncertainties over diverse space weather conditions. A storm‐time comparison shows that HASDM‐ML also supplies meaningful uncertainty estimates during extreme geomagnetic events.

Forecasting global and multi-level thermospheric neutral density and ionospheric electron content by tuning models against satellite-based accelerometer measurements

Global estimation of thermospheric neutral density (TND) on various altitudes is important for geodetic and space weather applications. This is typically provided by models, however, the quality of these models is limited due to their imperfect structure and the sensitivity of their parameters to the calibration period. Here, we present an ensemble Kalman filter (EnKF)-based calibration and data assimilation (C/DA) technique that updates the model’s states and simultaneously calibrates its key parameters. Its application is demonstrated using the TND estimates from on-board accelerometer measurements, e.g., those of the Gravity Recovery and Climate Experiment (GRACE) mission (at sim 410 km altitude), as observation, and the frequently used empirical model NRLMSISE-00. The C/DA is applied here to re-calibrate the model parameters including those controlling the influence of solar radiation and geomagnetic activity as well as those related to the calculation of exospheric temperature. The resulting model, called here ‘C/DA-NRLMSISE-00’, is then used to now-cast TNDs and individual neutral mass compositions for 3 h, where the model with calibrated parameters is run again during the assimilation period. C/DA-NRLMSISE-00 is also used to forecast the next 21 h, where no new observations are introduced. These forecasts are unique because they are available globally and on various altitudes (300–600 km). To introduce the impact of the thermosphere on estimating ionospheric parameters, the coupled physics-based model TIE-GCM is run by replacing the O2, O1, He and neutral temperature estimates of the C/DA-NRLMSISE-00. Then, the non-assimilated outputs of electron density (Ne) and total electron content (TEC) are validated against independent measurements. Assessing the forecasts of TNDs with those along the Swarm-A (sim 467 km), -B (sim 521 km), and -C (sim 467 km) orbits shows that the root-mean-square error (RMSE) is considerably reduced by 51, 57 and 54%, respectively. We find improvement of 30.92% for forecasting Ne and 26.48% for TEC compared to the radio occulation and global ionosphere maps (GIM), respectively. The presented C/DA approach is recommended for the short-term global multi-level thermosphere and enhanced ionosphere forecasting applications.

Impact of soft electron precipitation on the thermospheric neutral mass density during geomagnetic storms: GITM simulations

Impact of soft electron precipitation on the thermospheric neutral mass density during geomagnetic storms: GITM simulations

Impact of soft electron precipitation on the thermospheric neutral mass density during geomagnetic storms: GITM simulations

Impact of soft electron precipitation on the thermospheric neutral mass density during geomagnetic storms: GITM simulations

Impact of soft electron precipitation on the thermospheric neutral mass density during two intense geomagnetic storms: GITM simulations

Impact of soft electron precipitation on the thermospheric neutral mass density during two intense geomagnetic storms: GITM simulations

The Relationship Between Large Scale Thermospheric Density Enhancements and the Spatial Distribution of Poynting Flux

AbstractLarge thermospheric neutral density enhancements in the cusp region have been examined for many years. The Challenging Minisatellite Payload (CHAMP) satellite for example has enabled many observations of the perturbation, showing that it is mesoscale in size and exists statistically over solar cycle timescales. Further studies examining the relationship with magnetospheric energy input have shown that fine‐scale Poynting fluxes are associated with the density perturbations on a case‐by‐case basis, whilst others have found that mesoscale downward fluxes also exist in the cusp region statistically. In this study, we use nearly 8 years of the overlapping Super Dual Auroral Radar Network and Active Magnetosphere and Planetary Electrodynamics Response Experiment datasets to generate global‐scale patterns of the high‐latitude and height‐integrated Poynting flux into the ionosphere, with a time resolution of 2 min. From these, average patterns are generated based on the interplanetary magnetic field orientation. We show the cusp is indeed an important feature in the Poynting flux maps, but the magnitude does not correlate well with statistical neutral mass density perturbations observed by the CHAMP satellite on similar spatial scales. Importantly, the lack of correlation between mesoscale height‐integrated Poynting fluxes and the cusp neutral mass density enhancement gives possible insight into other processes that may account for the discrepancy, such as energy deposition at finer scale sizes or at higher altitudes than captured.