07 Apr 2022
07 Apr 2022
Status: this preprint is currently under review for the journal ESSD.

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

Xiangyue Chen1, Hongchao Zuo1, Zipeng Zhang2, Xiaoyi Cao1, Jikai Duan1, Jingzhe Wang3, Chuanmei Zhu2, and Zhe Zhang2 Xiangyue Chen et al.
  • 1College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000 China
  • 2Key Laboratory of Oasis Ecology, Xinjiang University, Xinjiang Urumqi 830046, China
  • 3MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China

Abstract. Aerosols are a complex compound with a great effect on the global radiation balance and climate system even human health, and concurrently are a large uncertain source in the numerical simulation process. The arid and semi-arid area has a fragile ecosystem, with abundant dust, but lacks related aerosol data or data accuracy. To solve these problems, we use the bagging trees ensemble model, based on 1 km aerosol optical depth (AOD) data and multiple environmental covariates, to produce monthly advanced-performance, full-coverage, and high-resolution (250 m) AOD products (named FEC AOD, Fusing Environmental Covariates AOD) in the arid and semi-arid areas. Then, based on FEC AOD, we analyzed the spatiotemporal pattern of AOD and further discussed the interpretation of environmental covariates to AOD. The result shows that the bagging trees ensemble model has a good performance, with its verification R2 always keeping at 0.90 and the R2 being 0.79 for FEC AOD compared with AERONET. The high AOD areas are located in the Taklimakan Desert and the Loess Plateau, and the low AOD area is concentrated in the south of Qinghai province. The higher the AOD is, the stronger the interannual variability. Interestingly, the AOD indicates a dramatic decrease in Loess Plateau and an evident increase in the southeast Taklimakan Desert, while the AOD in the southern Qinghai province almost shows no significant change between 2000 and 2019. The annual variation characteristics present that AOD is the largest in spring (0.267) and the smallest in autumn (0.147); the AOD pattern in Gansu province is bimodal, but unimodal in other provinces. The farmland and construction land are at high AOD levels compared with other land cover types. The meteorological factors demonstrate a maximum interpretation of AOD on all set temporal scales, followed by the terrain factors, and the surface properties are the smallest, i.e., 77.1 %, 59.1 %, and 50.4 % respectively on average. The capability of the environmental covariates for explained AOD varies with season, with an sequence being winter (86.6 %) > autumn (80.8 %) > spring (79.9 %) > summer (72.5 %). In this research, we pathbreakingly provide high spatial resolution (250 m) and long time series (2000–2019) FEC AOD dataset in arid and semi-arid regions to support the atmosphere and related study in northwest China, with the full data available at (Chen et al., 2021a).

Xiangyue Chen et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2021-426', Anonymous Referee #1, 30 May 2022
    • AC2: 'Comment on essd-2021-426', Xiangyue Chen, 19 Jul 2022
  • RC2: 'Comment on essd-2021-426', Anonymous Referee #2, 06 Jun 2022
    • AC3: 'Comment on essd-2021-426', Xiangyue Chen, 19 Jul 2022
  • AC1: 'Comment on essd-2021-426', Xiangyue Chen, 19 Jul 2022
  • AC2: 'Comment on essd-2021-426', Xiangyue Chen, 19 Jul 2022
  • AC3: 'Comment on essd-2021-426', Xiangyue Chen, 19 Jul 2022

Xiangyue Chen et al.

Data sets

High-resolution and full coverage AOD downscaling based on the bagging model over the arid and semi-arid areas, NW China Xiangyue Chen

Xiangyue Chen et al.


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Short summary
The arid and semi-arid areas are aerosol scarce data areas, we pathbreaking provide high resolution, full coverage and long time series AOD datasets (FEC AOD) to support the atmosphere and related study in northwest China. the FEC AOD effectively compensates for the deficiency and constraints of in-situ observation and satellite AOD products. Meanwhile, FEC AOD products demonstrate a reliable accuracy and ability to capture local information.