NDLI: Establishment of N $_{m}$ F $_{2}$ empirical model in the northern hemisphere based on COSMIC occultation data

Content Provider	Springer Nature Link
Author	Niu, Jun Fang, HanXian Weng, LiBin
Copyright Year	2014
Abstract	Ionospheric peak value of F2 layer (N $_{m}$ F $_{2}$) is an important parameter in the ionosphere, which has important applications in short-wave communication, ionospheric modeling and so on. In this paper, the empirical orthogonal function (EOF) decomposition method is used to analyze the N $_{m}$ F $_{2}$ obtained from the occultation data. Daily spatial distribution of N $_{m}$ F $_{2}$ at the same time is relatively even. Variance of first modal is much larger than the other modals. A local wavelet power spectrum (LWPS) method is applied to analysis the cycle of F $_{10.7}$ index and time coefficient of first modal. The result shows that they have similar cycle distribution, indicating that F $_{10.7}$ index is the main factor affecting variation of N $_{m}$ F $_{2}$. A function is established between the tine coefficient of first modal and F $_{10.7}$ index, average F $_{10.7}$ index value of early 81 days f $_{p}$ by least squares method. The results show that contribution coefficient of f $_{p}$ is negative which indicates that f $_{p}$ has an inert effect existing in the ionosphere. Contribution coefficient of F $_{10.7}$ is positive, which is consistent with the fact that it has an anomaly in winter/spring seasons. In summary, it is feasible to establish a mid-latitude empirical N $_{m}$ F $_{2}$ model in northern hemisphere based on occultation data and EOF decomposition method.
Starting Page	339
Ending Page	344
Page Count	6
File Format	PDF
ISSN	16747321
Journal	Science in China Series E: Technological Sciences
Volume Number	57
Issue Number	2
e-ISSN	18691900
Language	English
Publisher	Science China Press
Publisher Date	2014-01-24
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	empirical N $_{m}$ F $_{2}$ model empirical orthogonal function decomposition local wavelet power spectrum method least squares method Engineering
Content Type	Text
Resource Type	Article
Subject	Engineering Materials Science

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