Retrieval of total and fine mode aerosol optical depth by an improved MODIS Dark Target algorithm. (August 2022)

• Record Type: Journal Article
• Authors: Su, Xin; Wang, Lunche; Gui, Xuan; Yang, Leiku; Li, Lei; Zhang, Ming; Qin, Wenmin; Tao, Minghui; Wang, Shaoqiang; Wang, Lizhe
• Is Part Of: Environment international. Volume 166(2022)
• Publication Date: 2022-08
• Subjects: Dark Target algorithm -- Surface reflectance -- Fine mode fraction -- Fine mode aerosol optical depth -- Land General Aerosol algorithm; Environmental protection -- Periodicals; Environmental health -- Periodicals; Environmental monitoring -- Periodicals; Environmental Monitoring -- Periodicals; Environnement -- Protection -- Périodiques; Hygiène du milieu -- Périodiques; Environnement -- Surveillance -- Périodiques; Environmental health; Environmental monitoring; Environmental protection; Periodicals; 333.705
• DOI: 10.1016/j.envint.2022.107343
• Languages: English
• ISSNs: 0160-4120

Abstract

Abstract: Total and fine mode aerosol optical depth (AODT and AODF), as well as the fine mode fraction (FMF = AODF/AODT), are critical variables for climate change and atmospheric environment studies. The retrievals with high accuracy from satellite observations, particularly FMF and AODF over land, remain challenging. This study aims to improve the Moderate-resolution Imaging Spectro-radiometer (MODIS) land dark target (DT) algorithm for retrieving AODT, AODF, and FMF on a global scale. Based on the fact that the underestimated surface reflectance (SR) could overestimate the AODT and underestimate the aerosol size parameter in the DT algorithm, two robust schemes were developed to improve SR determination: the first (NEW1 DT) used the top of the atmosphere reflectance instead of SR at 2.12 µm; the second (NEW2 DT) used eleven-year MODIS data to establish a monthly spectral SR relationship model (2.12–0.47 and 2.12–0.65 µm) database at pixel-by-pixel scale. Then a novel lookup table approach based on the physical process was proposed to retrieve the AODF and FMF. The new MODIS AODT, FMF, and AODF were compared to AERosol RObotic NETwork (AERONET) retrievals. Results showed that the root mean square error (RMSE) was 0.096–0.103, 0.098–0.099, and 0.167–0.180 for the new AODTs, AODFs, and FMFs, respectively, which were better than that of the Collection 6.1 (C6.1) DT (0.117, 0.235, and 0.426) in the validation by global AERONET sites. From the validation results, NEW2 DT provided better AODT and coarse mode AOD retrievals, while NEW1 DT had better AODF and FMF performances. The spatial patterns of AODF, FMF, and AODC of the new DT algorithms were comparable to those of the Polarization and Directionality of the Earth's Reflectances aerosol product. Hence, the new algorithms have the potential to provide global AODT, FMF, and AODF products over land to the scientific community with high accuracy using long-term MODIS data.