In Low Earth Orbit (LEO), atmospheric drag is the largest contributor to trajectory prediction error. The current thermospheric density model used by the Combined Space Operations Center (CSpOC) in operations is the High Accuracy Satellite Drag Model (HASDM). Since HASDM is not available for use outside of the US Government, satellite operators are left to determine what publicly available, open-source density model they should integrate into their internal operational software. This decision is nontrivial due to the number of available density models, each having variable performance dependent on several factors including space weather conditions and orbit altitude. To compound matters, the rapid rise of this solar cycle suggests that the predicted solar maximum between 2024-2027 could be higher than the previous solar maximum, thus causing larger perturbations due to drag from atmospheric density on LEO satellites. Given the evermore challenging nature of operations in LEO, it is imperative for satellite operators to update legacy density models to a state-of-the-art density model to provide improved trajectory predictions for collision risk assessment and vital day-to-day operational decisions. This paper outlines several operations-ready thermospheric density models, describing their performance, computation time, required operational space weather input parameters, and notes for implementation. We define an operations-ready density model as a model that is well-documented, has verified and quantified model performance, and provides publicly available model code for implementation on a user’s own system. Operations-ready models include the Drag Temperature Model (DTM), the Jacchia-Bowman 2008 (JB2008) model, the US Naval Research Laboratory Mass Spectrometer and Incoherent Scatter radar 2.0 (NRLMSIS 2.0) model, and the Thermosphere– Ionosphere–Electrodynamics General Circulation Model (TIE-GCM). US Government operational density models, HASDM and the Whole Atmosphere Model and Ionosphere Plasmasphere Electrodynamics (WAM-IPE) model, are included for comparison in the Analysis section. Models are evaluated against global HASDM density and local Gravity Recovery And Climate Experiment Follow-On (GRACE-FO) satellite accelerometer density data. A propagation analysis is also included in which model performance is compared during quiet and storm conditions and resulting LEO object trajectory prediction errors are quantified at various orbit altitudes. The analysis shows that any of the named operations-ready density models (DTM2020, JB2008, NRLMSIS 2.0, TIE-GCM) are a viable option for satellite operations. In addition to LEO satellite operators, the results from this paper are also informative for the transition of civilian space traffic coordination efforts out of CSpOC and into the Department of Commerce. @en

The quality and distribution in time and space of available atmospheric observations are crucial for the accuracy of semi-empirical thermosphere models. However, datasets can be inconsistent, and their qualities and resolutions are often unequal. The main thermospheric density datasets of this century are briefly described and then compared to each other when possible in order to quantify differences. Total mass densities used in the comparisons include all high-resolution CHAMP, GRACE and GOCE data, Swarm A, daily-mean Stella, global daily mean TLE densities, and the SET HASDM density database. The temperature data from TIMED-SABER are also reviewed. The recently updated daily-mean TLE densities (TLE2021) are 2–10 % smaller on average than the previous version (TLE2015). The differences are not constant offsets per altitude level, but fluctuations of up to 5 % are present. Compared to HASDM densities for 6 altitudes from 250 to 675 km, TLE2021 is 15–20 % smaller at 250 km, and then the difference diminishes with altitude to reach the same average value at 575 km. These mean differences also fluctuate by a few percent on time scales of months, to 10 % over half a solar cycle at 575 km. The TLE2021 and HASDM densities are larger than the accelerometer-inferred CHAMP, GRACE and GOCE densities and average offsets are 10–15 % and 10–20 %, respectively. The comparison to Swarm-A and Swarm-B showed mean offsets of 10 % and less, with significant positive trends seen in the comparison with HASDM. Finally, largest differences are found for Stella and HASDM at 800 km, up to 45 % with strong semiannual variations. This study clearly shows that the available density data cannot be simply assimilated or combined without first accurately calibrating the data. The HASDM database is a valuable asset due to its considerable coverage in space and time, but its uncertainty and true resolution are not well understood and are still being evaluated. Data compatibility requires employing physically accurate and harmonized aerodynamic force models in the density derivation procedure, which is presently not achieved. The accuracy of the procedure, independent of the quality of the instrument (GNSS receiver, ground-based orbit determination, or accelerometer), inevitably decreases with altitude due to weakening of the drag signal to noise ratio. The TIMED-SABER instrument provides measurements of pressure and temperature in the lower thermosphere. SABER temperature uncertainty is well-known. The SABER dataset now exceeds twenty years and has been continuously operating that entire time. It was ingested in NRLMSIS 2.0 and comparisons show the much-improved fit in comparison with NRLMSISE-00. The lower thermosphere temperatures significantly modify density at higher altitudes, and its measurement is essential for modeling and assessment.

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Satellite drag modeling remains the largest source of uncertainty affecting space operations in low Earth orbit. The uncertainty stems from inaccurate models for mass density and drag coefficient. Drag coefficient modeling also impacts scientific knowledge on the physics and dynamics of the upper atmosphere through the estimation of high-fidelity mass density from measurements of acceleration on-board satellites. Efforts over the last decade have pushed drag coefficient modeling in the right direction, however, have resulted in multiple methods and tools. We provide a comprehensive review of the drag coefficient modeling methods and tools. Current scale differences between thermospheric data sets mostly originate from errors in the aerodynamic modeling, specifically in the modeling of the satellite outer surface geometry and the gas-surface interactions. Enhancing these models’ accuracy is intrinsically connected to the satellite drag fidelity for science and operations. A team of invested scientists recently met under the community-driven International Space Weather Action Teams (ISWAT) initiative to discuss and consolidate the efforts towards a drag coefficient modeling baseline for consistency in science and operations. In this paper, we compare the available methods for drag coefficient modeling, their impact on the derived density estimates, and make recommendations for adoption of baseline methods for science and operations. Results show that the differences in derived densities estimates can reach tens of percent at altitudes above 4̃50 km during solar minimum conditions resulting mainly from differences in the modeling of gas-surface interactions. As a result, we conclude and recommend that robust uncertainty quantification be an integral part of any modeling efforts that employ the high-fidelity accelerometer derived density estimates. We also conclude and recommend that gas-surface interaction models that account for impact of altitude and solar variations be employed moving forward. Finally, we recommend future science missions to improve our understanding of gas-surface interactions and eventually the upper thermosphere variability.

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The primary mechanism through which energy and momentum are transferred from the lower atmosphere to the thermosphere is through the generation and propagation of atmospheric waves. It is becoming increasingly evident that a few waves from the tropical wave spectrum preferentially propagate into the thermosphere and contribute to modify satellite drag. Two of the more prominent and well-established tropical waves are Kelvin waves: the eastward-propagating 3-day ultra-fast Kelvin wave (UFKW) and the eastward-propagating diurnal tide with zonal wave number 3 (DE3). In this work, Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) temperatures at 110 km and Gravity field and steady-state Ocean Circulation Explorer (GOCE) neutral densities and cross-track winds near 260 km are used to demonstrate vertical coupling in this height regime due to the UFKW and DE3. Significant inter- and intra-annual variability is found in DE3 and the UFKW, with evidence of latitudinal broadening and filtering of the latitude structures with height due to the effect of dissipation and mean winds. Additionally, anti-correlation between the vertical penetration of these waves to the middle thermosphere and solar activity level is established and explained through the effect of molecular dissipation.

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Meridional winds in the thermosphere are key to understanding latitudinal coupling and thermosphere-ionosphere coupling, and yet global measurements of this wind component are scarce. In this work, neutral and electron densities measured by the Challenging Minisatellite Payload (CHAMP) satellite at solar low and geomagnetically quiet conditions are converted to pressure gradient and ion drag forces, which are then used to solve the horizontal momentum equation to estimate low latitude to midlatitude zonal and meridional "synthetic" winds. We validate the method by showing that neutral and electron densities output from National Center for Atmospheric Research (NCAR) Thermosphere Ionosphere Mesosphere Electrodynamics-General Circulation Model (TIME-GCM) can be used to derive solutions to the momentum equations that replicate reasonably well (over 85% of the variance) the winds self-consistently calculated within the TIME-GCM. CHAMP cross-track winds are found to share over 65% of the variance with the synthetic zonal winds, providing further reassurance that this wind product should provide credible results. Comparisons with the Horizontal Wind Model 14 (HWM14) show that the empirical model largely underestimates wind speeds and does not reproduce much of the observed variability. Additionally, in this work we reveal the longitude, latitude, local time, and seasonal variability in the winds; show evidence of ionosphere-thermosphere (IT) coupling, with enhanced postsunset eastward winds due to depleted ion drag; demonstrate superrotation speeds of ∼27 m/s at the equator; discuss vertical wave coupling due the diurnal eastward propagating tide with zonal wave number 3 and the semidiurnal eastward propagating tide with zonal wave number 2.@en

Contemporary theory, modeling, and first-principles simulations indicate that dissipation of gravity waves (GW) plays an important role in modifying the mean circulation, thermal structure, and composition of the thermosphere. GW can propagate into the thermosphere from various sources in the lower atmosphere, deposit energy, and momentum into the thermosphere, and thereby modify its mean circulation, thermal structure and composition. However, measurements that verify or constrain predictions of GW propagation well into the thermosphere, especially on a global basis, are extremely limited. In this paper total mass densities and cross-track winds between 230 and 280 km derived from accelerometer measurements on the Gravity Field and Ocean Circulation Earth Explorer (GOCE) satellite between November 2009 and October 2013 are used to reveal the global morphology of horizontal structures between 128 km and 640 km, which are assumed to mainly reflect the presence of GW. The zonal-mean RMS variability at these scales is quantified in terms of seasonal-latitudinal dependences and dawn-dusk differences, which are interpreted in terms of current theoretical and modeling results. Little evidence is found for any longitude variability that can be attributed to specific source regions, except at high latitudes where polar/auroral sources and magnetic control dominate and near the Andes and the Antarctic Peninsula during local winter.

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This study is focused on the effect of solar flux conditions on the dynamics of gravity waves (GWs) in the thermosphere. Air density and crosswind in situ estimates from the Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) accelerometers are analyzed for the whole mission duration. The analysis is performed in the Fourier spectral domain averaging spectral results over periods of 2 months close to solstices. A new GW marker (called C³ _f) is introduced here to characterize GWs activity under low, medium, and high solar flux conditions, showing a clear solar damping effect on GW activity. Most GW signal is found in a spectral range above 8 mHz in GOCE data, meaning a maximum horizontal wavelength of around 1000 km. The level of GW activity at GOCE altitude is strongly decreasing with increasing solar flux. Furthermore, a shift in the dominant frequency with solar flux conditions has been noted, leading to larger horizontal wavelengths (from 200 to 500 km) during high solar flux conditions. The correlation between air density variability and GW marker allows to identify most of the large-amplitude perturbations below 67° latitudes as due to GWs. The influence of correlated error sources, between air density and crosswinds, is discussed. Consistency of the spectral domain results is verified in the time domain with a global mapping of high-frequency air density perturbations along the GOCE orbit. This analysis shows a clear dependence with geomagnetic latitude with strong perturbations at magnetic poles and an extension to lower latitudes favored by low solar activity conditions. These results are consistent with previous Challenging Minisatellite Payload (CHAMP) data analysis and with general circulation models.

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