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  Diagnostics of Es Layer Scintillation Observations Using FS3/COSMIC Data: Dependence on Sampling Spatial Scale

Tsai, L.-C., Su, S.-Y., Liu, C.-H., Schuh, H., Wickert, J., Alizadeh, M. M. (2021): Diagnostics of Es Layer Scintillation Observations Using FS3/COSMIC Data: Dependence on Sampling Spatial Scale. - Remote Sensing, 13, 18, 3732.
https://doi.org/10.3390/rs13183732

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Tsai, Lung-Chih1, Author
Su, Shin-Yi1, Author
Liu, Chao-Han1, Author
Schuh, H.2, Author              
Wickert, J.2, Author              
Alizadeh, Mohamad Mahdi1, Author
Affiliations:
1External Organizations, ou_persistent22              
21.1 Space Geodetic Techniques, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146025              

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 Abstract: The basic theory and experimental results of amplitude scintillation from GPS/GNSS radio occultation (RO) observations on sporadic E (Es) layers are reported in this study. Considering an Es layer to be not a “thin” irregularity slab on limb viewing, we characterized the corresponding electron density fluctuations as a power-law function and applied the Ryton approximation to simulate spatial spectrum of amplitude fluctuations. The scintillation index S4 and normalized signal amplitude standard deviation S2 are calculated depending on the sampling spatial scale. The theoretical results show that both S4 and S2 values become saturated when the sampling spatial scale is less than the first Fresnel zone (FFZ), and S4 and S2 values could be underestimated and approximately proportional to the logarithm of sampled spatial wave numbers up to the FFZ wave number. This was verified by experimental analyses using the 50 Hz and de-sampled FormoSat-3/Constellation Observing System for Meteorology, Ionosphere and Climate (FS3/COSMIC) GPS RO data in the cases of weak, moderate, and strong scintillations. The results show that the measured S2 and S4 values have a very high correlation coefficient of >0.97 and a ratio of ~0.5 under both complete and undersampling conditions, and complete S4 and S2 values can be derived by dividing the measured undersampling S4 and S2 values by a factor of 0.8 when using 1-Hz RO data.

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Language(s): eng - English
 Dates: 2021-09-172021
 Publication Status: Finally published
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.3390/rs13183732
OATYPE: Gold Open Access
GFZPOF: p4 T1 Atmosphere
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Title: Remote Sensing
Source Genre: Journal, SCI, Scopus, OA
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Pages: - Volume / Issue: 13 (18) Sequence Number: 3732 Start / End Page: - Identifier: CoNE: https://gfzpublic.gfz-potsdam.de/cone/journals/resource/journals426
Publisher: MDPI