This study presents a comprehensive comparison of the impact of solar activity on forecasting the upper atmosphere through assimilation of radio occultation (RO)-derived electron density (Ne) into a physics-based model (TIE-GCM) using an ensemble Kalman filter (KF). Globally abundant RO-derived Ne offers one of the most promising means to test the effect of assimilation on the model forecasted state on a global scale. This study emphasizes the importance of understanding how the assimilation results vary with solar activity, which is one of the main drivers of thermosphere-ionosphere dynamics. This study validates the forecast states with independent RO-derived GRACE (Gravity Recovery and Climate Experiment mission) Ne data. The principal result of the study is that the agreement between forecast Ne and data is better during solar minimum than solar maximum. The results also show that the agreement between data and forecast is mostly better than that of the standalone TIE-GCM driven with observed geophysical indices. The results emphasize that TIE-GCM significantly underestimate Ne in altitudes below 250 km and the assimilation of Ne is not as effective in these lower altitudes as it is in higher altitudes. The results demonstrate that assimilation of Ne significantly impacts the neutral mass density estimates via the KF state vector—the impact is larger during solar maximum than solar minimum relative to a control case that does not assimilate Ne. The results are useful to explain the inherent model bias, to understand the limitations of the data, and to demonstrate the capability of the assimilation technique.

中文翻译：

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太阳活动对电子密度数据同化对上层大气预报的影响

这项研究通过使用集成卡尔曼滤波器（KF）将无线电掩星（RO）得出的电子密度（Ne）吸收到基于物理的模型（TIE-GCM）中，对太阳活动对预测高层大气的影响进行了全面比较。）。在全球范围内，丰富的RO来源的Ne提供了一种最有前途的方法来测试同化对模型预测状态的影响。这项研究强调理解同化结果如何随太阳活动变化的重要性，这是热球-电离层动力学的主要驱动力之一。这项研究使用独立的RO衍生的GRACE（重力恢复和气候实验任务）Ne验证了预测状态数据。该研究的主要结果是，在太阳最低时，预报Ne和数据之间的一致性比太阳最高时更好。结果还表明，数据和预报之间的一致性主要好于由观测地球物理指数驱动的独立TIE-GCM。结果强调，TIE-GCM在250 km以下的海拔高度显着低估了Ne，Ne的同化作用在这些较低的海拔上不如在较高的海拔上有效。结果表明，Ne的同化通过KF状态向量显着影响中性质量密度估计-与未同化的对照例相比，在太阳最大期间的影响大于太阳最小期间的影响Ne。结果对于解释固有的模型偏差，了解数据的局限性以及证明同化技术的功能很有用。