Analysis of the evolution of the density of the lower thermosphere

Abstract

The warming effect of greenhouse gases at Earth's surface is well established, but this behavior changes with altitude. There is the hypothesis that, instead, in the thermosphere, increasing CO_2 concentrations produce a net cooling, which causes the region to contract and leads to a decrease in density at fixed altitudes. This effect combines with those that solar activity has on the thermospheric density and may have substantial practical implications for satellite lifetimes and the management of space debris. The aim of this thesis was to better characterize the evolution of thermospheric density trends, analyzing their consistency and dependence on factors like solar irradiance and CO_2 concentration. We adapted, tested, and validated the computational method developed by Martínez-Calzado in his 2023 Master's thesis, which served as the central algorithm in our methodology. The MATLAB code takes as input satellite Two Line Element (TLE) data, which are freely available online, and by using a propagator, returns density values that can then be compared to atmospheric models, in our case, NRLMSISE-00. The methodology was validated against the model mentioned above, and the results were compared to previous studies, which showed adequate agreement. We extended our density results with historic density values found in other studies, to reveal an average long-term density decrease of -4.58 %/decade from 1967 to 2025. This slope is smaller than earlier studies (around -5 to -5.5%/decade), likely due to the inclusion of recent solar maximum years, which temporarily raised mean densities. Our results also revealed correlations between density variations and solar irradiance, which challenge the exclusive importance of CO_2 concentrations to regulate thermospheric density. This underlines the importance of solar activity in modulating long-term trends. However, the overall decreasing trend of the thermospheric density at the considered altitudes, and the increasing antropogenc CO_2 concentrations deserve further quantitative analysis. In conclusion, we found that our applied methodology is robust and yields valuable results. The thesis demonstrated that the simple and publicly available TLE datasets can be processed to derive scientifically meaningful density values. The computational simplicity of the method lends itself to extending this research in the future with longer and larger datasets. Future work should incorporate newer atmospheric models and explore the combined influence of solar activity and rising SCO_2 concentrations.

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