Abstract
Abstract. Forecasting the thermosphere (the atmosphere's uppermost layer, from about 90 to 800 km altitude) is crucial to space-related applications, from space mission design to re-entry operations, space surveillance and more. Thermospheric dynamics is directly linked to the solar dynamics through the solar UV (ultraviolet) input, which is highly variable, and through the solar wind and plasma fluxes impacting Earth's magnetosphere. The solar input is non-periodic and non-stationary, with long-term modulations from the solar rotation and the solar cycle and impulsive components, due to magnetic storms. Proxies of the solar input exist and may be used to forecast the thermosphere, such as the F10.7 radio flux and the Mg II EUV (extreme-ultraviolet) flux. They relate to physical processes of the solar atmosphere. Other indices, such as the Ap geomagnetic index, connect with Earth's geomagnetic environment. We analyse the proxies' time series comparing them with in situ density data from the ESA (European Space Agency) GOCE (Gravity Field and Steady-State Ocean Circulation Explorer) gravity mission, operational from March 2009 to November 2013, therefore covering the full rising phase of solar cycle 24, exposing the entire dynamic range of the solar input. We use empirical mode decomposition (EMD), an analysis technique appropriate to non-periodic, multi-scale signals. Data are taken at an altitude of 260 km, exceptionally low for a low-Earth-orbit (LEO) satellite, where density variations are the single most important perturbation to satellite dynamics. We show that the synthesized signal from optimally selected combinations of proxy basis functions, notably Mg II for the solar flux and Ap for the plasma component, shows a very good agreement with thermospheric data obtained by GOCE, during periods of low and medium solar activity. In periods of maximum solar activity, density enhancements are also well represented. The Mg II index proves to be, in general, a better proxy than the F10.7 index for modelling the solar flux because of its specific response to the UV spectrum, whose variations have the largest impact over thermospheric density.
Highlights
We show that the synthesized signal from optimally selected combinations of proxy basis functions, notably Mg II for the solar flux and Ap for the plasma component, shows a very good agreement with thermospheric data obtained by GOCE, during periods of low and medium solar activity
Forecasting the thermosphere is crucial to space mission design, re-entry operations and space surveillance applications
The orbital decay rate of satellites depends on atmospheric drag, which is directly affected by the variable solar activity (Masutti et al, 2016)
Summary
Forecasting the thermosphere is crucial to space mission design, re-entry operations and space surveillance applications. The orbital decay rate of satellites depends on atmospheric drag, which is directly affected by the variable solar activity (Masutti et al, 2016). Current semi-empirical models of the thermosphere, such as NRLMSISE-00 (Picone et al, 2002) and JB2008 (Bowman et al, 2008), include satellite drag data, mostly available between 400 and 600 km height, and solar proxies. The NRLMSISE-00 model includes, for instance, the F10.7 solar flux (present and averaged over the previous 81 d) and the Ap index for the previous 57 h These models, though, may prove inaccurate in predicting neutral thermospheric density, depending on the level of solar activity We shall use the low-altitude GOCE data which have become available since that cited analysis (Bruinsma et al, 2014)
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