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Remote Sensing
Volume 15
Issue 6
10.3390/rs15061584
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Article

A Multi-Model Ensemble Pattern Method to Estimate the Refractive Index Structure Parameter Profile and Integrated Astronomical Parameters in the Atmosphere

by
Hanjiu Zhang
1,2,3,
Liming Zhu
2,3,4,
Gang Sun
2,3,4,*,
Kun Zhang
2,3,
Ying Liu
1,2,3,
Xuebin Ma
2,3,4,
Haojia Zhang
2,3,4,
Qing Liu
2,3,
Shengcheng Cui
2,3,4,
Tao Luo
2,3,4,
Xuebin Li
2,3,4 and
Ningquan Weng
1,2,3,4
1
School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China
2
Advanced Laser Technology Laboratory of Anhui Province, Hefei 230037, China
3
Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science (HFIPS), Chinese Academy of Sciences, Hefei 230031, China
4
Science Island Branch of Graduate School, University of Science and Technology of China, Hefei 230026, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2023, 15(6), 1584; https://doi.org/10.3390/rs15061584
Submission received: 15 February 2023 / Revised: 5 March 2023 / Accepted: 9 March 2023 / Published: 14 March 2023
(This article belongs to the Special Issue Advanced Satellite Remote Sensing Techniques for Meteorological, Climate and Hydroscience Studies)
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Abstract

In this study, we devised a constraint method, called multi-model ensemble pattern (MEP), to estimate the refractive index structure parameter (Cn2) profiles based on observational data and multiple existing models. We verified this approach against radiosonde data from field campaigns in China’s eastern and northern coastal areas. Multi-dimensional statistical evaluations for the Cn2 profiles and integrated astronomical parameters have proved MEP’s relatively reliable performance in estimating optical turbulence in the atmosphere. The correlation coefficients of MEP and measurement overall Cn2 in two areas are up to 0.65 and 0.76. A much higher correlation can be found for a single radiosonde profile. Meanwhile, the difference evaluation of integrated astronomical parameters also shows its relatively robust performance compared to a single model. The prowess of this reliable approach allows us to carry out regional investigation on optical turbulence features with routine meteorological data soon.
Keywords: optical turbulence; refractive index structure parameter; vertical profile; radiosonde; routine meteorological parameters; multi-model ensemble pattern; integrated astronomical parameters optical turbulence; refractive index structure parameter; vertical profile; radiosonde; routine meteorological parameters; multi-model ensemble pattern; integrated astronomical parameters
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MDPI and ACS Style

Zhang, H.; Zhu, L.; Sun, G.; Zhang, K.; Liu, Y.; Ma, X.; Zhang, H.; Liu, Q.; Cui, S.; Luo, T.; et al. A Multi-Model Ensemble Pattern Method to Estimate the Refractive Index Structure Parameter Profile and Integrated Astronomical Parameters in the Atmosphere. Remote Sens. 2023, 15, 1584. https://doi.org/10.3390/rs15061584

AMA Style

Zhang H, Zhu L, Sun G, Zhang K, Liu Y, Ma X, Zhang H, Liu Q, Cui S, Luo T, et al. A Multi-Model Ensemble Pattern Method to Estimate the Refractive Index Structure Parameter Profile and Integrated Astronomical Parameters in the Atmosphere. Remote Sensing. 2023; 15(6):1584. https://doi.org/10.3390/rs15061584

Chicago/Turabian Style

Zhang, Hanjiu, Liming Zhu, Gang Sun, Kun Zhang, Ying Liu, Xuebin Ma, Haojia Zhang, Qing Liu, Shengcheng Cui, Tao Luo, and et al. 2023. "A Multi-Model Ensemble Pattern Method to Estimate the Refractive Index Structure Parameter Profile and Integrated Astronomical Parameters in the Atmosphere" Remote Sensing 15, no. 6: 1584. https://doi.org/10.3390/rs15061584

APA Style

Zhang, H., Zhu, L., Sun, G., Zhang, K., Liu, Y., Ma, X., Zhang, H., Liu, Q., Cui, S., Luo, T., Li, X., & Weng, N. (2023). A Multi-Model Ensemble Pattern Method to Estimate the Refractive Index Structure Parameter Profile and Integrated Astronomical Parameters in the Atmosphere. Remote Sensing, 15(6), 1584. https://doi.org/10.3390/rs15061584

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