Accurate forecast of the thermospheric density is critical to the space community. The data assimilation approach that is based on the self‐consistent upper‐atmosphere model may provide better predictive capability of the coupled thermosphere system. In this study, a physics‐based assimilation system (hereafter referred to as PIDA) that is based on the Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model was used to validate the capability of reproducing the evolution of the global thermosphere state. The effective solar and geophysical drivers were estimated by ingesting neutral density from a single satellite into the PIDA. It was found that the PIDA can reproduce the temporal variation of the global thermospheric density at around the altitude where the orbit density was ingested. Furthermore, the PIDA is also capable of capturing the temporal evolution of the thermospheric density at various altitudes. However, a systematic bias, depending on altitude, is seen in the modeled neutral density of the PIDA. Moreover, this systematic bias in the thermospheric density is likely ascribed to the overestimation of the density in the lower thermosphere. Consequently, the spatial and temporal evolutions of the lower thermosphere under various conditions should be considered carefully in the physics‐based data assimilation system. Additionally, the assessments of the obtained results suggested that the observations of multiple parameters at different altitudes are required to be assimilated into the thermospheric model.

中文翻译：

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由单颗卫星的中性密度数据驱动的基于物理的数据同化系统的评估

准确预测热层密度对空间界至关重要。基于自洽的高层大气模型的数据同化方法可以为耦合的热层系统提供更好的预测能力。在这项研究中，基于热物理-电离层-电动力学总循环模型的基于物理的同化系统（以下称为PIDA）被用来验证再现全球热层状态演化的能力。通过将中性密度从单颗卫星吸收到PIDA中，可以估算出有效的太阳和地球物理驱动力。已经发现，PIDA可以再现在摄取轨道密度的高度附近的全球热层密度的时间变化。此外，PIDA还能够捕获不同高度的热层密度随时间的变化。但是，在模拟的PIDA中性密度中会看到取决于海拔的系统偏差。此外，热球密度的这种系统性偏差可能归因于较低热球中密度的高估。因此，在基于物理学的数据同化系统中，应仔细考虑下热圈在各种条件下的时空演化。另外，对获得的结果的评估表明，需要将不同高度的多个参数的观测结果同化到热层模型中。在PIDA的建模中性密度中可以看到。此外，热球密度的这种系统性偏差可能归因于对较低热球密度的过高估计。因此，在基于物理学的数据同化系统中，应仔细考虑下热圈在各种条件下的时空演化。另外，对获得的结果的评估表明，需要将不同高度的多个参数的观测结果同化到热层模型中。在PIDA的建模中性密度中可以看到。此外，热球密度的这种系统性偏差很可能归因于较低热球中密度的高估。因此，在基于物理学的数据同化系统中，应仔细考虑下热圈在各种条件下的时空演化。另外，对获得的结果的评估表明，需要将不同高度的多个参数的观测结果同化到热层模型中。在基于物理学的数据同化系统中，应仔细考虑下热圈在各种条件下的时空演化。另外，对获得的结果的评估表明，需要将不同高度的多个参数的观测结果同化到热层模型中。在基于物理学的数据同化系统中，应仔细考虑下热圈在各种条件下的时空演化。另外，对获得的结果的评估表明，需要将不同高度的多个参数的观测结果同化到热层模型中。