Improved merge schemes for MODIS Collection 6.1 Dark Target and Deep Blue combined aerosol products

Abstract

Our previous study illustrated that the operational Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 (C6.1) Dark Target (DT) and Deep Blue (DB) combined products (denoted as DTB0) are not always the best in most regions due to its unsuitable merge approach. Therefore, the objective of this study is to develop an improved merge approach to increase the spatiotemporal data coverage and reduce the estimation uncertainty. For this, three tests, i.e., a land-use-type test, a surface-relief test, and an aerosol-type test are performed according to the strengths and weakness of the performances of the DT and DB algorithms with their high-quality assurance retrievals (QA = 3 for DT and QA ≥ 2 for DB) against the newest Aerosol Robotic Network (AERONET) Version 3 Level 2.0 measurements. Based on this, new merged DT and DB products (denoted as DTB1) are generated. The Terra and Aqua DTB1 products are then validated against AERONET measurements at 286 sites on site, continental, and global scales, and for varying underlying surfaces and elevated terrains from 2013 to 2017. The DTB0 products for the same period are collected for comparison. More than 90% of the sites now have more data points, and the performances of the DTB1 products are improved with an increased percentage of the data falling within the expected error [±(0.05 + 15%)] envelope and reduced mean absolute errors and root-mean-square errors compared with DTB0 products at most sites. Separate- and equal-number comparisons show that the DTB1 products significantly improve both the data coverage and data quality. The new merged products are more accurate and less affected by varying surface structures than the operational products. These results suggest that the improved merge approach is more robust and can be used for generating more accurate global aerosol products.