Articles | Volume 14, issue 12
Data description paper
30 Nov 2022
Data description paper |  | 30 Nov 2022

Full-coverage 250 m monthly aerosol optical depth dataset (2000–2019) amended with environmental covariates by an ensemble machine learning model over arid and semi-arid areas, NW China

Xiangyue Chen, Hongchao Zuo, Zipeng Zhang, Xiaoyi Cao, Jikai Duan, Chuanmei Zhu, Zhe Zhang, and Jingzhe Wang

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Revised manuscript not accepted

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Cited articles

Ali, M. A. and Assiri, M.: Analysis of AOD from MODIS-Merged DT–DB Products Over the Arabian Peninsula, Earth Syst. Environ., 3, 625–636,, 2019. 
Ali, G., Bao, Y., Boiyo, R., Tang, W., Lu, Q., and Min, J.: Evaluating MODIS and MISR aerosol optical depth retrievals over environmentally distinct sites in Pakistan, J. Atmos. Solar-Terr. Phy., 183, 19–35,, 2019. 
Almazroui, M.: A comparison study between AOD data from MODIS deep blue collections 51 and 06 and from AERONET over Saudi Arabia, Atmos. Res., 225, 88–95,, 2019. 
Ångström, A.: The parameters of atmospheric turbidity, Tellus, 16, 64–75,, 1964. 
Bilal, M., Nichol, J. E., and Wang, L.: New customized methods for improvement of the MODIS C6 Dark Target and Deep Blue merged aerosol product, Remote Sens. Environ., 197, 115–124,, 2017. 
Short summary
Arid and semi-arid areas are data-scarce aerosol areas. We provide path-breaking, high-resolution, full coverage, and long time series AOD datasets (FEC AOD) to support the atmosphere and related studies in northwestern China. The FEC AOD effectively compensates for the deficiency and constraints of in situ observations and satellite AOD products. Meanwhile, FEC AOD products demonstrate a reliable accuracy and ability to capture long-term change information.