4.7 Article

Validation of Himawari-8 aerosol optical depth retrievals over China

期刊

ATMOSPHERIC ENVIRONMENT
卷 199, 期 -, 页码 32-44

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.atmosenv.2018.11.024

关键词

Aerosol optical depth; Himawari-8; Validation; MODIS

资金

  1. National Key Research and Development Programs of China [2017YFB0502805]
  2. Natural Science Foundation of Zhejiang Province [LQ18D010004]
  3. National Natural Science Foundation of China [41801258]
  4. National Institute for Environmental Studies (NIES)

向作者/读者索取更多资源

High temporal resolution (every 10 min) aerosol observations are rarely provided by satellite sensors. The Advanced Himawari Imager (AHI) aboard Himawari-8 can provide aerosol optical depth (AOD) over China with this frequency. The sensor provides great opportunity to retrieve the particle matter near the ground and improve air quality modeling using the aerosol products. However, there is still lack of quality validation about AHI AOD. A comprehensive research was conducted to evaluate the performance of AHI aerosol products based on sixteen sun-photometers stations in AErosol RObotic NETwork (AERONET) and Sun-Sky Radiometer Observation Network (SONET) over China. The overall comparison of AHI AOD and ground AOD shows a high correlation (R-2 = 0.67). However, there is only 55% of AHI AOD falling in the expected error envelops ( +/- 0.05 +/- 0.2*AOD( ground)). AOD bias between AHI AOD and ground AOD increases with the AOD magnitude. The accuracy of AHI AOD is also highly depend on seasons and surface land cover types. Best performance of AHI aerosol retrievals is shown in summer and for urban region. The diurnal variability validation shows that AHI AOD catch the diurnal AOD variations well, especially for summer. Large differences between AHI AOD and MODerate-resolution Imaging Spectrometer (MODIS) aerosol products are shown, especially for northwest China. The analysis indicates that the uncertainties of AHI aerosol retrievals are induced by large errors of aerosol models and surface reflectance estimation in the algorithm.

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