Accuracy assessment of MODIS land aerosol optical thickness algorithms using AERONET measurements over North America

The planned simultaneous availability of visible and near-IR observations from the geostationary platforms of Tropospheric Emissions: Monitoring of Pollution (TEMPO) and Geostationary Operational Environmental Satellites (GOES) 16/17 Advanced Base Imager (ABI) will present the opportunity of deriving an accurate aerosol product taking advantage of both ABI's high spatial resolution in the visible range and TEMPO's sensitivity to aerosol absorption in the near-UV range. Because the wavelengths of ABI are similar to those of the Moderate Resolution Imaging Spectroradiometer (MODIS), existing aerosol algorithms of MODIS can be applied to ABI observations. In this work, we evaluate three distinct aerosol algorithms of MODIS deriving aerosol optical thickness (AOT) over land surfaces using visible and near-IR observations. The Dark Target (DT), Deep Blue (DB), and Multiangle Implementation of Atmospheric Correction (MAIAC) algorithms are all applied to the radiance measurements of MODIS on board the Aqua satellite. We have evaluated each algorithm by comparing the satellite-retrieved AOT to space-time collocated ground-based sun photometer measurements of the same parameter at 171 sites of the Aerosol Robotic Network (AERONET) over North America (NA). A spatiotemporal scheme collocating the satellite retrievals with the ground-based measurements was applied consistently to all three retrieval datasets. We find that the statistical performance of all three algorithms is comparable over darker surfaces over eastern NA with the MAIAC algorithm providing relatively better comparison over western NA sites characterized by inhomogeneous elevation and bright surfaces. The higher spatial resolution of the MAIAC product (1 km) allows a substantially larger number of matchups than DB 10 km and DT 10 km (DT 3 km) products by 115% and 120% (86 %), respectively, over eastern NA and by 150% and 220%(197 %) over western NA. The characterization of the error in AOT for the three aerosol products as a function of bidirectional surface reflectance derived from both MAIAC and an independent MOD09 atmospheric correction shows a systematic positive bias in DT retrievals over brighter surfaces, whereas DB and MAIAC retrievals show no such bias throughout the wide range of surface brightness, with MAIAC offering the lowest spread in errors. The results reported here represent an objective, unbiased evaluation of existing over-land aerosol retrieval algorithms of MODIS. The detailed statistical evaluation of the performance of each of these three algorithms may be used as guidance in the development of inversion schemes to derive aerosol properties from ABI or other MODIS-like sensors.