Parameter Retrieval of Transparent Cirrus Clouds over South China Sea Based on Artificial Neural Networks

Wenqiang Lu; Shizhi Yang; Tao Luo; Xuebin Li; Shengcheng Cui; Chen Cheng; Lu Han; Jianjun Shi; Yeyan Han

doi:10.3788/AOS230605

Acta Optica Sinica, Volume. 44, Issue 6, 0601001(2024)

Parameter Retrieval of Transparent Cirrus Clouds over South China Sea Based on Artificial Neural Networks

Wenqiang Lu^1,2,3, Shizhi Yang^1,2,3、*, Tao Luo^1,2,3, Xuebin Li^1,2,3, Shengcheng Cui^1,2,3, Chen Cheng^2,5, Lu Han^2,4, Jianjun Shi^1,2,3, and Yeyan Han^1,2,3

Author Affiliations

¹Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, Anhui , China

²Science Island Branch of Graduate School, University of Science and Technology of China, Hefei 230026, Anhui , China

³Advanced Laser Technology Laboratory of Anhui Province, Hefei 230037, Anhui , China

⁴Center for Fundamental Science Research, Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, Anhui , China

⁵Key Laboratory of Optical Calibration and Characterization, Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, Anhui , China

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Figures & Tables(15)

Fig. 1. Data processing flowchart

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Fig. 2. Histograms of transparent cirrus cloud optical depth and top height. (a) Transparent cirrus cloud optical depth; (b) top height of cirrus cloud

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Fig. 3. ROC curve of probability of detection $P_{O D}$ and rate of false alarm $P_{O D}$ ,and probability of detection $P_{O D}$ varying with transparent cirrus optical depth. (a) ROC curve; (b) probability of detection $P_{O D}$ varying with transparent cirrus optical depth

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Fig. 4. M_PE and $M_{A P E}$ of optical depth and top height of transparent cirrus clouds. (a) M_PE of optical depth; (b) M_PEof top height; (c) $M_{A P E}$ of optical depth; (d) $M_{A P E}$ _{of top height}

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Fig. 5. M_PE and M_APEvarying with optical depth and top height. (a) Optical depth; (b) top height

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Fig. 6. Scatter plots of predicted values and true values. (a) Optical depth; (b) top height

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$MODIS cloud fraction and CALIOP trajectory (line)$

Fig. 7. MODIS cloud fraction and CALIOP trajectory (line)

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$Distributions of MODIS cloud fraction. (a) Before detection; (b) after detection$

Fig. 8. Distributions of MODIS cloud fraction. (a) Before detection; (b) after detection

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Fig. 9. Comparison of detection results. (a) MODIS clear sky observation results; (b) detected results of neural network; (c) CALIOP observation results

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Fig. 10. Comparison of inverse values and true values. (a) Optical depth; (b) top height

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Fig. 11. Transparent cirrus clouds undetected by MODIS

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Fig. 12. Distributions of optical depth and top height of transparent cirrus clouds undetected by MODIS. (a) Optical depth; (b) top height

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Table 1. MODIS correction coefficients for infrared bands

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Table 1. MODIS correction coefficients for infrared bands

Band No.	$λ / μ m$	F_scale /10^-4	d_offset
27	6.715	1.178	2724.218
28	7.325	1.924	2317.488
29	8.550	5.571	2610.015
30	9.730	4.063	1560.333
31	11.030	6.508	2035.933
32	12.020	5.710	2119.085
33	13.335	2.623	2500.599
34	13.635	2.009	2499.094
35	13.935	1.768	2500.521
36	14.235	1.186	2495.891

Table 2. Confusion matrix
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Table 2. Confusion matrix
Item Predicted value
Transparent cirrus clouds Clear sky
True value Transparent cirrus clouds 28873 $(N_{T P})$ 7509 $(N_{F N})$
Clear sky 2716 $(N_{F P})$ 24881 $(N_{T N})$

Table 3. Comparison of results of related algorithms
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Table 3. Comparison of results of related algorithms
Algorithm $R_{M S E}$ / $R$
Optical depth Top height
Algorithm proposed by Kox et al. 0.24/0.61 0.71 km/0.82
Algorithm proposed by Strandgren et al. Not given/0.65 Not given/0.90
Ours 0.25/0.79 0.74 km/0.87

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Wenqiang Lu, Shizhi Yang, Tao Luo, Xuebin Li, Shengcheng Cui, Chen Cheng, Lu Han, Jianjun Shi, Yeyan Han. Parameter Retrieval of Transparent Cirrus Clouds over South China Sea Based on Artificial Neural Networks[J]. Acta Optica Sinica, 2024, 44(6): 0601001

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