Characterization and application of artificial light sources for nighttime aerosol optical depth retrievals using the Visible Infrared Imager Radiometer Suite Day/Night Band
<p>Using nighttime observations from Visible Infrared Imager Radiometer Suite (VIIRS) Day/Night band (DNB), the characteristics of artificial light sources are evaluated as functions of observation conditions, and incremental improvements are documented on nighttime aerosol retrievals using VI...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2019-06-01
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| Series: | Atmospheric Measurement Techniques |
| Online Access: | https://www.atmos-meas-tech.net/12/3209/2019/amt-12-3209-2019.pdf |
| Summary: | <p>Using nighttime observations from Visible Infrared Imager Radiometer Suite
(VIIRS) Day/Night band (DNB), the characteristics of artificial light
sources are evaluated as functions of observation conditions, and incremental
improvements are documented on nighttime aerosol retrievals using VIIRS DNB
data on a regional scale. We find that the standard deviation of
instantaneous radiance for a given artificial light source is strongly
dependent upon the satellite viewing angle but is weakly dependent on lunar
fraction and lunar angle. Retrieval of nighttime aerosol optical thickness
(AOT) based on the novel use of these artificial light sources is
demonstrated for three selected regions (United States, Middle East and
India) during 2015. Reasonable agreement is found between nighttime AOTs
from the VIIRS DNB and temporally adjacent daytime AOTs from the AErosol RObotic
NETwork (AERONET) as well as from coincident nighttime AOT retrievals from
the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), indicating
the potential of this method to begin filling critical gaps in diurnal AOT
information at both regional and global scales. Issues related to cloud,
snow and ice contamination during the winter season, as well as data loss
due to the misclassification of thick aerosol plumes as clouds, must be
addressed to make the algorithm operationally robust.</p> |
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| ISSN: | 1867-1381 1867-8548 |