研究目的
To monitor the stability of the high gain stage (HGS) of the VIIRS day/night band (DNB) using nighttime observations over the Dome C site under moonlight, by developing a corrected lunar irradiance model and a BRDF model to remove angular dependencies.
研究成果
The study successfully monitors the radiometric stability of VIIRS DNB HGS, showing a 5.44-5.49% lower reflectance in 2012 due to RSR changes, with long-term stability better than 1.58% from 2013 to 2016. The developed MT-SWC lunar irradiance model and nighttime BRDF model effectively remove lunar phase and angular dependencies, providing a method applicable to other low-light sensors.
研究不足
Limitations include the use of a first-order linear model for MT2009 correction due to limited SeaWiFS data, calibration uncertainties in VIIRS DNB HGS, and the use of prelaunch RSR for 2012 data adding uncertainty. Atmospheric effects are not fully accounted for, especially at high lunar zenith angles.
1：Experimental Design and Method Selection:
The study uses the Dome C site for vicarious calibration under moonlight. The MT2009 lunar irradiance model is corrected using SeaWiFS lunar observations to differentiate waxing and waning phases (MT-SWC model). A TOA BRDF model is developed to account for angular dependencies in reflectance.
2：Sample Selection and Data Sources:
VIIRS DNB data from 2012 to 2017 are used, processed by NOAA's IDPS and archived in CLASS. Observations are selected based on criteria including lunar phase angle <90 degrees, solar zenith angle >118 degrees, spatial uniformity <5%, and lunar zenith angle <80 degrees. SeaWiFS lunar observations are used for model correction.
3：List of Experimental Equipment and Materials:
VIIRS DNB sensor on Suomi-NPP spacecraft, SeaWiFS sensor on SeaStar spacecraft, Dome C site in Antarctica.
4：Experimental Procedures and Operational Workflow:
Data selection, reflectance retrieval using lunar irradiance models, correction of MT2009 model with SeaWiFS data, BRDF modeling, normalization to remove angular effects, and stability analysis.
5：Data Analysis Methods:
Statistical analysis including mean, standard deviation, and uncertainty calculations; least squares fitting for model parameters; comparison with reference models like Hudson BRDF and MCD43A1 product.
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