当前位置: X-MOL 学术Radio Sci. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Data Assimilation Retrieval of Electron Density Profiles From Ionosonde Virtual Height Data
Radio Science ( IF 1.6 ) Pub Date : 2021-04-16 , DOI: 10.1029/2021rs007264
Victoriya V. Forsythe 1 , Irfan Azeem 1 , Ryan Blay 1 , Geoff Crowley 1 , Roman A. Makarevich 1 , Wanli Wu 1
Affiliation  

A new method is developed to retrieve electron density profiles from a raw virtual height ionosonde traces. A Kalman filter is used for the assimilative inversion scheme together with the newly developed data‐driven vertical covariance model. The detailed mathematical formalism for the derivation of the Jacobian that takes into account the effect of the magnetic field is presented. The incoherent scatter radar measurements from Arecibo observatory are employed as the known truth to simulate the virtual height data. The results show that the data assimilative inversion technique accurately retrieves the vertical structure of the ionospheric density at the bottom side of the profile and reconstructs the vertical and temporal small‐scale density variations. A comparison with the results obtained by the POLynomial ANalysis (POLAN) inversion algorithm is presented. The assimilative inversion systematically outperforms the accuracy of the POLAN algorithm, on average reducing the percent errors in the electron density by half. Additionally, the simultaneous data ingestion is compared to the sequential assimilation of the virtual height data.

中文翻译:

从离子探空仪虚拟高度数据获取电子密度剖面的数据同化

开发了一种新方法,可从原始的虚拟高度离子探空仪迹线中检索电子密度分布。卡尔曼滤波器用于同化反演方案,以及新开发的数据驱动的垂直协方差模型。给出了考虑磁场影响的雅可比方程推导的详细数学形式。来自阿雷西博天文台的非相干散射雷达测量结果被用作模拟虚拟高度数据的已知事实。结果表明,数据同化反演技术准确地提取了剖面底部电离层密度的垂直结构,并重建了垂直和时间的小尺度密度变化。提出了与POLynomial AAnalysis(POLAN)反演算法获得的结果的比较。同化反演系统地胜过POLAN算法的准确性,平均将电子密度的误差百分比降低了一半。另外,将同时摄取的数据与虚拟高度数据的顺序同化进行比较。
更新日期:2021-04-29
down
wechat
bug