Abstract
The Visible Infrared Imaging Radiometer Suite (VIIRS) has been observing aerosol optical depth (AOD), which is a critical parameter in air pollution and climate change, for more than 7 years since 2012. Due to limited and uneven distribution of the Aerosol Robotic Network (AERONET) station in China, the independent data from the Campaign on Atmospheric Aerosol Research Network of China (CARE-China) was used to evaluate the National Oceanic and Atmospheric Administration (NOAA) VIIRS AOD products in six typical sites and analyze the influence of the aerosol model selection process in five subregions, particularly for dust. Compared with ground-based observations, the performance of all retrievals (except the Shapotou (SPT) site) is similar to other previous studies on a global scale. However, the results illustrate that the AOD retrievals with the dust model showed poor consistency with a regression equation as y = 0.312x + 0.086, while the retrievals obtained from the other models perform much better with a regression equation as y = 0.783x + 0.119. The poor AOD retrieval with the dust model was also verified by a comparison with the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol product. The results show they have a lower correlation coefficient (R) and a higher mean relative error (MRE) when the aerosol model used in the retrieval is identified as dust. According to the Ultraviolet Aerosol Index (UVAI), the frequency of dust type over southern China is inconsistent with the actual atmospheric condition. In addition, a comparison of ground-based Ångström exponent (α) values yields an unexpected result that the dust model percentage exceed 40% when α < 1.0, and the mean α shows a high value of ~0.75. Meanwhile, the α peak value (~1.1) of the “dust” model determined by a satellite retravel algorithm indicate there is some problem in the dust model selection process. This mismatching of the aerosol model may partly explain the low accuracy at the SPT and the systemic biases in regional and global validations.
Highlights
Aerosols play a critical role in environment and climate [1,2,3], and they are associated with atmospheric pollution that has a considerable impact on human health [4,5]
The basic hypothesis of the Dark Target (DT) algorithm is the linear relationship in surface reflectance over dense vegetation between visible and shortwave infrared bands [46]
The SPT site, which is located in a semiarid area, and the Yantai Coast (YTC) site, which is located in a coastal city, have unfavorable surface characteristics for Aerosol optical depth (AOD) retrievals
Summary
Aerosols play a critical role in environment and climate [1,2,3], and they are associated with atmospheric pollution that has a considerable impact on human health [4,5]. The aerosol components are complex and vary with time and location; if the VIIRS algorithm uses a wrong aerosol model that cannot characterize the real aerosol physical and chemical properties, the AOD might be retrieved improperly. Recent research described a potential aerosol model selection issue in the VIIRS AOD algorithm [28]. On this day, large differences were observed in the AOD distribution between RthemeoMte SOenDs.I2S02a0n, 1d2,V99I1IRS products. Unreal high AOD values (inside the red ellipse in Figure 1e3)oaf r1e8 retrieved by VIIRS algorithm; similar conditions could be observed on other days. SPT (Figure 1c) performed the worst, with almost retrievals falling below the Remote Sens. 2020, 12, 991
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