在整个太阳周期23和24期间用资料同化评估热层模拟的性能
Assessing the performance of thermospheric modelling with data assimilation throughout solar cycles 23 and 24
摘要：
作为欧盟框架包7 ATMOP项目的一部分，利用卫星密度测量为热层模型开发了资料同化程序。两个模型进行了研究，一个是大气环流模型，TIEGCM，和其他半经验的阻力温度模型，DTM。运行使用资料同化与这些模型的结果进行了比较，独立的密度观测CHAMP和GRACE卫星在整个太阳活动周期23和24。在太阳活动极小期和极大期，包括2003年的太阳风暴，对60天的时间周期进行了研究。物理模型和半经验模型之间的差异已被表征。结果表明，这两种模型往往表现出类似的行为，低估了太阳能极大值时的密度，高估了太阳能极小值时的密度。DTM在太阳极小期表现更好，两种模型在太阳极大期的准确性都较低。使用TIEGCM进行资料同化，平均改善约4%。随着进一步改进，在实际空间天气预报中使用大气环流模型（除了目前使用的经验方法之外）是可行的。今后的工作将允许对热层数据进行近实时同化，以改进预报。
英文摘要：
Data assimilation procedures have been developed for thermospheric models using satellite density measurements as part of the EU Framework Package 7 ATMOP Project. Two models were studied; one a general circulation model, TIEGCM, and the other a semi-empirical drag temperature model, DTM. Results of runs using data assimilation with these models were compared with independent density observations from CHAMP and GRACE satellites throughout solar cycles 23 and 24. Time periods of 60 days were examined at solar minimum and maximum, including the 2003 Hallowe'en storms. The differences between the physical and the semi-empirical models have been characterised. Results indicate that both models tend to show similar behaviour; underestimating densities at solar maximum, and overestimating them at solar minimum. DTM performed better at solar minimum, with both models less accurate at solar maximum. A mean improvement of ~4% was found using data assimilation with TIEGCM. With further improvements, the use of general circulation models in operational space weather forecasting (in addition to empirical methods currently used) is plausible. Future work will allow near-real-time assimilation of thermospheric data for improved forecasting.
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