Validation, Stability, and Consistency of MODIS Collection 6.1 and VIIRS Version 1 Deep Blue Aerosol Data Over Land

Abstract

The Deep Blue (DB) algorithm has been used to retrieve aerosol optical depth (AOD) and Ångström exponent (AE) over land from multiple satellite instruments, including the Moderate Resolution Imaging Spectroradiometers (MODIS) aboard the Terra and Aqua platforms and the Visible Infrared Imaging Radiometer Suite (VIIRS). This study first validates the latest MODIS (Collection 6.1) and VIIRS (Version 1) DB data products against Aerosol Robotic Network observations. On global average, the typical level of uncertainty in AOD is slightly better than ±(0.05 + 20%) relative to Aerosol Robotic Network. AE is quantitatively more uncertain but qualitatively shows skill at distinguishing between fine‐mode and coarse‐mode dominated aerosol columns. Results are also compared with the previous MODIS Collection 6. The stability of the three DB data sets ranges from 0.005–0.01 AOD per decade. Second, spatial and temporal patterns in AOD and AE are compared between the three data sets. It is found that they all show similar patterns of spatial coverage, which is predominantly linked to cloud cover, snow, and polar night. Regional time series of AOD also show highly consistent seasonal and interannual variations and are strongly correlated, although have offsets in some regions due to a combination of algorithmic and sensor‐related differences.

Spatiotemporal Trends of Aerosols over Urban Regions in Pakistan and Their Possible Links to Meteorological Parameters

“…In an attempt to analyze AOD trends utilizing MODIS Aqua and Terra data over Indian subcontinent Srivastava et al [72] have reported that trends estimated from various techniques are comparable for both the datasets. In a recent study by Sayer et al [66], it is reported that the overall performance of DB applied to MODIS Terra and Aqua is similar. However, based on the stability of AERONET AOD data, the MODIS sensors onboard the Terra and Aqua platforms are suffering from artificial drifts in AOD retrievals.…”

“…Two algorithms, namely the Dark target (DT) and deep blue (DB), are used to retrieve AOD over land and ocean [34,35,63]. The latest MODIS Collection 6.1 (C061) incorporates several improvements in the retrieval algorithms and the uncertainties have been effectively mitigated as compared to the previous collections [47,[64][65][66]. More details on data products, retrieval algorithms, calibration, and uncertainties can be found in related studies [34,35,63,[66][67][68][69].…”

VIIRS Deep Blue Aerosol Products Over Land: Extending the EOS Long‐Term Aerosol Data Records

“…Journal of Geophysical Research: Atmospheres serve as a brief overview and demonstration of the general quality of the data; a full detailed validation is provided by Sayer et al (2019). In brief, this analysis follows previous DB evaluation papers such as Sayer et al (2013) by averaging satellite retrievals whose pixel centers fall within 25 km of AERONET sites and comparing with AERONET data averaged within 30 min of the satellite overpass.…”

How should we aggregate data? Methods accounting for the numerical distributions, with an assessment of aerosol optical depth

“…This quadratic formulation is more robust to calibration problems in individual channels than a linear twochannel interpolation. It also reflects the fact that the relationship between log(τ ) and log(λ) is not linear but shows curvature dependent on fine-mode particle size (Eck et al, 1999;Schuster et al, 2006). When more than two wavelengths are available, this is a more realistic description of the spectral derivative of AOD than the bispectral approximation in Eq.…”