Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD retrievals against ground sunphotometer observations over East Asia

Abstract

Abstract. Persistent high aerosol loadings together with extremely high population densities have raised serious air quality and public health concerns in many urban centers in East Asia. However, ground-based air quality monitoring is relatively limited in this area. Recently, satellite-retrieved Aerosol Optical Depth (AOD) at high resolution has become a powerful tool to characterize aerosol patterns in space and time. Using ground AOD observations from the Aerosol Robotic Network (AERONET) and the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-Asia Campaign, as well as from handheld sunphotometers, we evaluated emerging aerosol products from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP), the Geostationary Ocean Color Imager (GOCI) aboard the Communication, Ocean, and Meteorology Satellite (COMS), and Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) (Collection 6) in East Asia in 2012 and 2013. In the case study in Beijing, when compared with AOD observations from handheld sunphotometers, 51 % of VIIRS Environmental Data Record (EDR) AOD, 37 % of GOCI AOD, 33 % of VIIRS Intermediate Product (IP) AOD, 26 % of Terra MODIS C6 3 km AOD, and 16 % of Aqua MODIS C6 3 km AOD fell within the reference expected error (EE) envelope (±0.05 ± 0.15 AOD). Comparing against AERONET AOD over the Japan-South Korea region, 64 % of EDR, 37 % of IP, 61 % of GOCI, 39 % of Terra MODIS, and 56 % of Aqua MODIS C6 3 km AOD fell within the EE. In general, satellite aerosol products performed better in tracking the day-to-day variability than tracking the spatial variability at high resolutions. The VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and MODIS C6 3 km products had positive biases.

Validation of VIIRS AOD through a Comparison with a Sun Photometer and MODIS AODs over Wuhan

“…2017, 9, 403 5 of 13 [17]. However, this result was inconsistent with a previous validation study, in which 32% of VIIRS IP retrievals fell into the EE, with a slightly low R 2 of 0.63, and a relatively large positive bias (0.25) in Beijing within 3 km around AERONET [24]. The different aerosol types may have caused this difference between Beijing and Wuhan.…”

“…According to suggestions from other research groups [16,22,24], data matching was performed with the following rules. First, the mean AOD was averaged when at least 20% of the pixels fell within the sampling box.…”

GOCI Yonsei aerosol retrieval version 2 products: an improved algorithm and error analysis with uncertainty estimation from 5-year validation over East Asia

“…Because it has more channels with higher spatial resolution in the visible and near-infrared (NIR) bands compared with recent and planned advanced meteorological sensors in GEO, including the Advanced Himawari Imager (AHI), the Advanced Baseline Imager (ABI), and the Advanced Meteorological Imager (AMI), GOCI provides valuable information related to AOPs. Hourly AOD from the GOCI YAER algorithm is in good agreement with Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD over East Asia (Xiao et al, 2016). The application of GOCI retrievals through data assimilation results in improved performance of several air quality forecasting model predictions of AOD and PM concentrations (Park et al, 2014;Saide et al, 2014;Jeon et al, 2016;Lee et al, 2017).…”

Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

“…They also concluded that the merged product does not specifically outperform the DT or DB results. The Terra C6 3 km AOD product was validated by Xiao et al (2016) using AERONET data from the DRAGON Asia campaign (2012-2013) (Holben et al, 2017) and over Beijing using hand-held sun photometers. Tao et al (2015) evaluated MODIS/Aqua C6 AOD over different regions in China for both DB and DT products, but not for the merged DTDB AOD, using AERONET data as reference.…”

“…Xu et al, 2015;Ma et al, 2016; but also using multiple satellite data (Lin et al, 2010;Guo et al, 2011Guo et al, , 2016bDong et al, 2017;Zhao et al, 2017;Zhang et al, 2017). However, these studies used MODIS C5.1 AOD data and substantial differences exist between C6 and C5.1 (e.g., Levy et al, 2013;Sayer et al, 2014;Tao et al, 2015;Xiao et al, 2016). Furthermore, in addition to data sets over dark and brighter surfaces from the DT and DB algorithms, respectively, C6 also provides a merged DTDB data set based on criteria using the quality flags in each product .…”