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.

中文翻译：

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低热层对太阳活动的响应：GOCE 2009-2012 数据的经验模式分解分析

摘要。预测热层（大气的最上层，大约 90 至 800 公里的高度）对于与空间相关的应用至关重要，从空间任务设计到再入操作、空间监视等。热层动力学通过高度可变的太阳 UV（紫外线）输入以及影响地球磁层的太阳风和等离子体通量与太阳动力学直接相关。由于磁暴，太阳能输入是非周期性和非平稳的，具有来自太阳自转和太阳周期以及脉冲分量的长期调制。存在太阳输入的代理，可用于预测热层，例如 F10.7 无线电通量和 Mg II EUV（极紫外）通量。它们与太阳大气的物理过程有关。其他指数，如Ap地磁指数，与地球地磁环境有关。我们分析了代理的时间序列，将它们与来自 2009 年 3 月至 2013 年 11 月运行的 ESA（欧洲航天局）GOCE（重力场和稳态海洋环流探测器）重力任务的原位密度数据进行比较，因此涵盖了整个上升过程。太阳周期的第 24 阶段，暴露了太阳输入的整个动态范围。我们使用经验模式分解 (EMD)，这是一种适用于非周期性、多尺度信号的分析技术。数据是在 260 公里的高度采集的，这对于低地球轨道 (LEO) 卫星来说是异常低的，其中密度变化是对卫星动力学最重要的扰动。我们展示了来自最佳选择的代理基函数组合的合成信号，尤其是太阳通量的 Mg II 和等离子体分量的 Ap 显示出与 GOCE 获得的热层数据非常吻合，在中低太阳活动期间。在太阳活动最大的时期，密度增强也有很好的表现。一般来说，Mg II 指数被证明是比 F10.7 指数更好的模拟太阳通量的指标，因为它对紫外线光谱有特定的响应，紫外线光谱的变化对热层密度的影响最大。