Analysis of Near Sea-Surface Optical Turbulence Characters Based on Hilbert-Huang Transform

Hanjiu Zhang; Gang Sun; Kun Zhang; Yang Wu; Feifei Wang; Xuebin Li; Shengcheng Cui; Qing Liu; Ningquan Weng

doi:10.3788/LOP202259.1201001

Journals >Laser & Optoelectronics Progress >Volume 59 >Issue 12 >Page 1201001 > Article

Laser & Optoelectronics Progress
Vol. 59, Issue 12, 1201001 (2022)

Analysis of Near Sea-Surface Optical Turbulence Characters Based on Hilbert-Huang Transform

Hanjiu Zhang^1、2, Gang Sun^2、*, Kun Zhang^1、2, Yang Wu^1、2, Feifei Wang², Xuebin Li², Shengcheng Cui², Qing Liu², and Ningquan Weng^1、2

Author Affiliations

¹School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, Anhui , China

²Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, Anhui , China

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DOI: 10.3788/LOP202259.1201001 Cite this Article Set citation alerts

Hanjiu Zhang, Gang Sun, Kun Zhang, Yang Wu, Feifei Wang, Xuebin Li, Shengcheng Cui, Qing Liu, Ningquan Weng. Analysis of Near Sea-Surface Optical Turbulence Characters Based on Hilbert-Huang Transform[J]. Laser & Optoelectronics Progress, 2022, 59(12): 1201001 Copy Citation Text

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$Instrument and Cn2 daily change. (a) Instrument installation environment; (b) daily change of refractive index structure constant on November 16, 2019$

Fig. 1. Instrument and

C_{n}^{2}

daily change. (a) Instrument installation environment; (b) daily change of refractive index structure constant on November 16, 2019

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IMF and IMF frequency spectra. (a) Cn2 time series and corresponding IMF at noon on November 16, 2019; (b) IMF FFT frequency spectra

Fig. 2. IMF and IMF frequency spectra. (a)

C_{n}^{2}

time series and corresponding IMF at noon on November 16, 2019; (b) IMF FFT frequency spectra

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Fig. 3. Relationship between m and T of IMF. (a) m-T; (b) m-lnT

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Fig. 4. IMF reconstruction with different scales and corresponding relation with original signal. (a)(b) Different IMF combinations; (c)(d) relation between reconstructed combination and original signal

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Fig. 5. Spectrum analysis. (a) Time-frequency-energy distribution of IMF obtained by HHT; (b) HHT marginal spectrum and FFT spectrum; (c) normalized marginal spectra of meteorological elements and

C_{n}^{2}

in unstable layer condition; (d) as Fig.5(c) but in stable layer condition

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Parameter	IMF1	IMF2	IMF3	IMF4	IMF5	IMF6	IMF7	IMF8	R
Correlation	0.67	0.43	0.33	0.27	0.26	0.15	0.10	0.02	0.13
Period number	246	119.5	60	29.5	11.5	5	2.5	1
Period /s	14.263	30.13	60	122.03	313.04	720	1440	3600
Energy /（10^-28·m^-4/9·s）	1.15	2.45	1.98	1.35	2.31	14.45	33.80	9.80	3.96
Mean energy /（10^-31·m^-4/9·s）	4.68	20.50	33.08	45.83	201.04	2890	13520	9800

Table 1. Character analysis of each IMF

Combination	11.02	11.07	11.09	11.11	11.13	11.21	11.22	11.26
IMF2‒IMF9	0.043	0.118	0.152	0.211	0.041	0.069	0.040	0.073
IMF3‒IMF9	0.068	0.114	0.161	0.212	0.062	0.085	0.065	0.110
IMF4‒IMF9	0.079	0.140	0.177	0.246	0.083	0.095	0.071	0.129
IMF5‒IMF9	0.075	0.235	0.150	0.297	0.088	0.095	0.067	0.136
IMF6‒IMF9	0.071	0.153	0.142	0.297	0.086	0.094	0.068	0.136
IMF7‒IMF9	0.062	0.195	0.145	0.234	0.074	0.056	0.030	0.217

Table 2. RMSE of IMF combinations in many days

Cross correlation coefficient	Daytime		Night
Cross correlation coefficient	All scales	log₁₀T≥2	All scales	log₁₀T≥2
R（ $C_{n}^{2}$ and humidity）	0.9012	0.8893	0.7493	0.4992
R（ $C_{n}^{2}$ and temperature）	0.8489	0.7350	0.7294	0.6102
R（ $C_{n}^{2}$ and wind speed）	0.8357	0.5520	0.7550	0.4554
R（temperature and wind speed）	0.9217	0.8534	0.9660	0.9609

Table 3. Cross correlation of meteorological elements and

C_{n}^{2}

marginal spectra

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