Effect of Middle Atmosphere density variability on re-entering objects
Abstract
As interest grows for atmospheric reentry for increased precision on trajectory and heating rate, errors remain due to atmospheric density uncertainty. Most reentry models do not take into account variability in the middle atmosphere, but use instead climatologies which fail to encompass the daily variability of density and temperature. This work endeavours to propose initial computations of density-induced reentry variability using lidar-based middle-atmosphere data to investigate which reentry configurations are sensitive to the atmospheric variability. Winter density data ranging from 30 to 80 km from the Observatoire de Haute-Provence (OHP, (43.9°N, 5.7°E)) were classified according to some extreme conditions, namely Winter Mesospheric Inversion Layers, Sudden Stratospheric Warmings, and a reference climatology model (MSIS-2.0) for quiet climatology. We obtained five different density products containing mean and standard deviation. We used a simplified aerodynamic reentry model to simulate the path of multiple objects of various sizes and initial speeds. Because of the time cost, results are obtained with a polynomial chaos approximation of the reentry model, using selected altitudes as random entry variables. The approached model matches Monte-Carlo simulations, with NRMSE typically below 3%, but reaching for some situations up to 7% Results first showed that the density had a clear effect on the reentry outputs and induced an uncertainty compared to the mean outputs computed with MSIS-2.0: for instance, density created an error of about 10 % for the minimum reentry angle, 1 m for the uncertainty of position when arriving at 30 km and about 4.5 % of the maximum heating rate (about 100 kW.m-2). Overall, the obtained distributions of trajectories, mass and speed were largely insensitive to the density product chosen. However, when considering specific thresholds or limit cases, extreme events such as SSWs caused noticeable deviations to the reference climatology, decreasing the number of bounces by a factor three (20% of cases compared to 6%), but increasing the number of trajectories deviating out of 1 m of the mean found with the reference climatology compared to winter typical variability (80% compared to 30%). These results suggest that density in the middle atmosphere, particularly during extreme events such as SSWs or MILs, could affect the re-entry, calling for a more refined middle atmosphere model which would take density variability into account.
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BibTeX
@article{tufel2026effect,
title = {{Effect of Middle Atmosphere density variability on re-entering objects}},
author = {Nicolas Gilbert Tufel and Philippe Keckhut and Laurent Dumas and Yann Courcoux and Marie Vicomte},
journal = {Advances in Space Research},
year = {2026},
month = oct,
doi = {10.1016/j.asr.2026.09.061},
url = {https://hal.science/hal-05780857v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Effect of Middle Atmosphere density variability on re-entering objects
AU - Nicolas Gilbert Tufel
AU - Philippe Keckhut
AU - Laurent Dumas
AU - Yann Courcoux
AU - Marie Vicomte
PY - 2026
DA - 2026/10/06
JO - Advances in Space Research
DO - 10.1016/j.asr.2026.09.061
UR - https://hal.science/hal-05780857v1
AB - As interest grows for atmospheric reentry for increased precision on trajectory and heating rate, errors remain due to atmospheric density uncertainty. Most reentry models do not take into account variability in the middle atmosphere, but use instead climatologies which fail to encompass the daily variability of density and temperature. This work endeavours to propose initial computations of density-induced reentry variability using lidar-based middle-atmosphere data to investigate which reentry configurations are sensitive to the atmospheric variability. Winter density data ranging from 30 to 80 km from the Observatoire de Haute-Provence (OHP, (43.9°N, 5.7°E)) were classified according to some extreme conditions, namely Winter Mesospheric Inversion Layers, Sudden Stratospheric Warmings, and a reference climatology model (MSIS-2.0) for quiet climatology. We obtained five different density products containing mean and standard deviation. We used a simplified aerodynamic reentry model to simulate the path of multiple objects of various sizes and initial speeds. Because of the time cost, results are obtained with a polynomial chaos approximation of the reentry model, using selected altitudes as random entry variables. The approached model matches Monte-Carlo simulations, with NRMSE typically below 3%, but reaching for some situations up to 7% Results first showed that the density had a clear effect on the reentry outputs and induced an uncertainty compared to the mean outputs computed with MSIS-2.0: for instance, density created an error of about 10 % for the minimum reentry angle, 1 m for the uncertainty of position when arriving at 30 km and about 4.5 % of the maximum heating rate (about 100 kW.m-2). Overall, the obtained distributions of trajectories, mass and speed were largely insensitive to the density product chosen. However, when considering specific thresholds or limit cases, extreme events such as SSWs caused noticeable deviations to the reference climatology, decreasing the number of bounces by a factor three (20% of cases compared to 6%), but increasing the number of trajectories deviating out of 1 m of the mean found with the reference climatology compared to winter typical variability (80% compared to 30%). These results suggest that density in the middle atmosphere, particularly during extreme events such as SSWs or MILs, could affect the re-entry, calling for a more refined middle atmosphere model which would take density variability into account.
SN - 0273-1177
SN - 1879-1948
ER -