Using the Dark Target retrieval algorithm to create a long-term and multiscale aerosol dataset

Aboard NASA's Terra (since 2000) and Aqua (since 2002) satellites, the Moderate resolution Imaging Spectroradiometer (MODIS) sensors have been observing the Earth in spectral bands that cover the wavelength range of reflected solar radiation. We have been applying the "dark-target" (DT) aerosol retrieval algorithm to derive aerosol optical depth (AOD) over land and ocean and Angstrom Exponent (AE) over ocean. Although providing similar views of global aerosol, in Collection 6 (C6), there are systematic differences between the two MODIS records. Assuming we can attribute the Terra/Aqua differences to sampling differences (AM vs PM) and calibration offsets, the MODIS 16-year dataset is still too short to robustly detect global aerosol trends. Therefore, we need additional sensors to continue, expand, and interpret the MODIS aerosol data records. By using consistent radiative transfer and other algorithm assumptions, we have ported DT to the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP (SNPP; launched 2011). As expected, the DT-VIIRS and C6-MODIS data records are qualitatively very similar. However, there are nearly 20% offsets between the two datasets that points to 2% offsets in calibration. Concurrent with trying to close the gaps between MODIS on Terra, MODIS on Aqua, and VIIRS on SNPP, we think about applying DT on other platforms. For example, by porting DT retrieval to MODIS Airborne Simulator (MAS; aboard aircraft since 1996), we may be able to use the factor-of-ten better spatial resolution to quantify cloud effects within MODIS pixels. By porting DT to the new generation of geostationary satellites (e.g. Advanced Imagers on Himawari and GOES-R), we can better quantify differences between the AM (Terra) and PM (Aqua) sensors. The goal, of course, is a multi-sensor aerosol dataset that is considered a climate data record.