Evaluation and comparison of MAIAC, DT and DB aerosol products over China

Abstract. A new Multiangle Implementation of Atmospheric Correction (MAIAC) algorithm has been applied in Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and recently provides globally high spatial resolution Aerosol Optical Depth (AOD) products at 1 km. Meanwhile, several improvements are modified in classical Dark Target (DT) and Deep Blue (DB) aerosol retrieval algorithms in MODIS collection 6.1 products. However, validation and comparison for MAIAC, DT and DB algorithms is still lacking in China. In this paper, a comprehensive assessment and comparison of AOD products at 550 nm wavelength based three aerosol retrieval algorithms in MODIS sensor using ground-truth measurements from Aerosol Robotic Network (AERONET) sites over China during 2000 to 2017 is presented. In general, after quality assurance (QA) filter, the coefficient of determination (R2=0.854), correlation coefficient (R=0.929), root-mean-square error (RMSE=0.178), mean bias (Bias=0.019) and the fraction fall within expected error (Within_EE=67.10 %, EE=±(0.05+0.15×AOD)) results for MAIAC algorithm show better accuracy than those from DT and DB algorithms. While the R2, R, RMSE, Bias and Within_EE of DT algorithm are 0.817, 0.930, 0.192, 0.077, 55.36 %, respectively, those corresponding statistics for DB algorithm are 0.827, 0.921, 0.190, 0.018, 63.32 %. Moreover, the spatiotemporal completeness for MAIAC (29.69 %) product is also better than DT (8.00 %) and DB (19.50 %) products after QA filter. In addition, the land type dependence characteristic, view geometry dependence, spatiotemporal retrieval accuracy and spatial variation pattern difference for three products are also analyzed in details.

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