Validation of MODIS and Deep Blue aerosol optical depth retrievals in an arid/semi-arid region of northwest China

Abstract The global aerosol optical depth (AOD or τ) has been retrieved using the Dark Target algorithm (the C004 and C005 products) and the Deep Blue algorithm (DB product). Few validations have thus far been performed in arid/semi-arid regions, especially in northwest China. The ground-based remote sensing of AOD from sun photometers at four sites in Xinjiang during the years 2002–2003 is used to validate aerosol products, including C004, C005 and DB of the Moderate Resolution Imaging Spectroradiometer (MODIS). The results show substantial improvement in the C005 aerosol product over the C004 product. The average correlation coefficient of regression with ground measurements increased from 0.59 to 0.69, and the average offset decreased from 0.28 to 0.13. The slopes of the linear regressions tended to be close to unity. The percentage of AODs falling within the retrieval errors of 30% (or △τ = ±0.1 ± 0.2τ) increased from 16.1% to 45.6%. The best retrievals are obtained over an oasis region, whereas the worst are obtained over urban areas. Both the MODIS C004 and C005 products overestimate AOD, which is likely related to improper assumptions of the aerosol model and of the estimation of surface reflectance. An encouraging result has been derived with regard to validation of the DB AOD. Overall, the average offset, slope and correlation coefficient of regression with sun-photometer measurements are −0.04, 0.88 and 0.85, respectively. Approximately 73% of the DB AOD retrievals fall within the expected error of 30%. Underestimation of the AOD by the DB products is observed. The aerosol model and estimations of surface reflectance in this region require further improvements.