Infrared and Laser Engineering, Volume. 52, Issue 1, 20220262(2023)
Influence of atmospheric models on the aerosol optical parameters inversion and classification
Figures & Tables(16)
Fig. 1. Methodological flow for studying the influence of atmoshpere model on the retrieval of aerosol optical parameters
Fig. 2. The use of different atmospheric models (GDAS and ERA5) for the case of the Lille site in France (8th May, 2020, 20:00 to 21:00 UTC) has an impact on the retrieval results. (a) Relative deviation of the atmospheric molecular number density; (b) Relative deviation of the aerosol extinction coefficient at 355 nm obtained by the Raman method; (c) Relative deviation of the aerosol backscatter coefficient at 355 nm obtained by the Raman method
Fig. 3. Mean relative deviation of aerosol extinction coefficient and molecular number density at 355 nm from four stations
Fig. 4. Relationship between the mean relative deviation of back-scatter coefficient and aerosol concentration
Fig. 5. Aerosol extinction coefficient obtained by Raman method using different atmospheric models
Fig. 6. Aerosol backscatter coefficient obtained by the Raman and elastic scattering methods using different models
Fig. 7. Aerosol lidar ratio and color ratio results of dual wavelength obtained by different atmospheric models
Fig. 8. Ångström exponent results retrieved by different atmospheric models
Fig. 9. 48 h backward trajectory of aerosol provided by HYSPLIT model
Table 1. Mean and standard deviation of typical values of aerosol type related characteristics
View tableView in ArticleTable 1. Mean and standard deviation of typical values of aerosol type related characteristics
Type $ {S}^{355} $ $ {S}^{532} $ $ {\kappa }_{\alpha }\left({355,532}\right) $ ${\kappa }_{\beta }\left({355,1\;064}\right)$ ${\kappa }_{\beta }\left({532,1\;064}\right)$ $ {\kappa }_{\beta }\left({355,532}\right) $ CC 50±8 41±6 1.7±0.6 1.0±0.2 1.0±0.3 1.3±0.3 PC 69±12 63±13 1.7±0.5 1.3±0.3 1.3±0.2 1.4±0.6 D 58±12 55±7 0.3±0.4 0.4±0.1 0.4±0.1 0.3±0.2 MD 42±4 47±6 0.5±0.3 0.5±0.2 0.4±0.3 0.7±0.3 PD 54±8 64±9 0.6±0.2 0.9±0.3 0.8±0.1 1.0±0.5 MM 25±7 24±8 0.9±0.3 0.8±0.1 0.8±0.2 1.0±0.3 S 81±16 78±11 1.3±0.3 1.3±0.1 1.3±0.1 1.2±0.3 V 50±11 48±13 0.2±0.3 0.1±0.1 0.4±0.3 0.2±0.3
Table 2. Basic information of EARLINET observing stations
View tableView in ArticleTable 2. Basic information of EARLINET observing stations
Lidar Elastic scattering/nm Raman/nm Institution 355 532 1 064 387 607 530 MUSA √ √ √ √ √ CNR-IMAA, Potenza, Italy LRD200 √ √ PollyXT √ √ √ √ √ TROPOS, Leipzig, Germany PAOLI √ √ √ √ √ Universidade de Évora, Portugal LILAS √ √ √ √ √ Université de Lille, France
Table 3. Vertical pressure levels of different model data
View tableView in ArticleTable 3. Vertical pressure levels of different model data
Dataset Vertical pressure levels ERA5 137 vertical levels from the surface to 0.02 hPa IFS_ECMWF 137 vertical levels from the surface to 0.01 hPa GDAS 23 vertical levels from the surface to 20 hPa
Table 4. Maximum deviation of different models for aerosol extinction coefficient obtained by Raman algorithm at different wavelengths and corresponding deviation of molecular number density from four stations
View tableView in ArticleTable 4. Maximum deviation of different models for aerosol extinction coefficient obtained by Raman algorithm at different wavelengths and corresponding deviation of molecular number density from four stations
Algorithm Raman method Wavelength/nm 355 532 Maximum deviation ${{D} }_{\alpha }$ 20.43% 19.44% Corresponding deviation $ {D}_{N} $ 0.59% 0.44%
Table 5. Maximum deviation of different models for backscatter obtained by two algorithms at different wavelengths and corresponding deviation of molecular number density from four stations
View tableView in ArticleTable 5. Maximum deviation of different models for backscatter obtained by two algorithms at different wavelengths and corresponding deviation of molecular number density from four stations
Algorithm Raman method Elastic scattering method Wavelength/nm 355 532 355 532 1064 Maximum deviation $ {D}_{\beta } $ −2.22% −2.27% 11.11% 4.80% 2.79% Corresponding deviation $ {D}_{N} $ −2.29% −2.16% −2.02% 0.20% 1.56%
Table 6. Maximum deviation, mean value and standard deviation in the low aerosol concentration region (IB < 0.0015 sr −1) at three wavelengths from four stations
View tableView in ArticleTable 6. Maximum deviation, mean value and standard deviation in the low aerosol concentration region (IB < 0.0015 sr −1) at three wavelengths from four stations
Statistics project Results 355 nm 532 nm 1064 nm Maximum deviation 11.11% 4.8% 2.79% Mean value 4.26% 1.58% 0.74% Standard deviation 2.80% 1.27% 1.24%
Table 7. Mean value and standard deviation of related parameters of aerosol type using different atmospheric models at an altitude of 1.5-2 km
View tableView in ArticleTable 7. Mean value and standard deviation of related parameters of aerosol type using different atmospheric models at an altitude of 1.5-2 km
Model Related parameters $ {\mathrm{\kappa }}_{\alpha }\left(\mathrm{355,532}\right) $ $ {\mathrm{\kappa }}_{\beta }\left(\mathrm{355,532}\right) $ ${\mathrm{\kappa } }_{\beta }\left(\mathrm{355,1\;064}\right)$ ${\mathrm{\kappa } }_{\beta }\left(\mathrm{532,1\;064}\right)$ $ {S}^{355} $ $ {S}^{532} $ ${ {Y} }\left(\mathrm{532,355}\right)$ GDAS 0.9±0.3 1.2±0.2 1.1±0.1 1.0±0.1 36±2 40±7 1.1±0.2 ERA5 0.8±0.3 1.2±0.2 1.1±0.1 1.0±0.1 39±2 45±6 1.1±0.2
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Yuanzu Wang, Dongsong Sun, Yuli Han, Jun Zheng, Yiming Zhao. Influence of atmospheric models on the aerosol optical parameters inversion and classification[J]. Infrared and Laser Engineering, 2023, 52(1): 20220262
Paper Information
Category: Atmospheric optics
Received: Apr. 18, 2022
Accepted: --
Published Online: Feb. 9, 2023
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