Assessing VIIRS aerosol data assimilation as a MODIS successor in the NASA GEOS system

Abstract. Aerosol data assimilation is critical for global Earth system modelling, improving aerosol optical depth (AOD) representation for weather and atmospheric composition forecasts and reanalyses. MODIS sensors on Terra and Aqua were the primary observation source for operational aerosol assimilation within the NASA Goddard Earth Observing System (GEOS). As MODIS nears decommission, VIIRS aboard NOAA satellites represent its successor. This transition trades the MODIS morning satellite for VIIRS’s increased data volume, gapless equatorial coverage, and finer spatial resolution. This study assesses the assimilation of VIIRS NOAA-20 AOD within GEOS.

To ensure observing platform consistency, GEOS uses a Neural Network Retrieval (NNR) algorithm translating radiances into AERONET-calibrated AOD, homogenizing aerosol observations before assimilation. Two experiments (March 2019–February 2020) compared a control assimilating NNR MODIS Terra/Aqua against a test assimilating NNR VIIRS NOAA-20.

Validation against AERONET and Maritime Aerosol Network observations shows that, despite lacking a morning satellite, VIIRS alone performs competitively with combined MODIS, with comparable correlations and error metrics. Relative performance varies by aerosol regime. In dust-dominated environments, VIIRS frequently yields better agreement with AERONET due to finer resolution and greater data volume. During biomass burning, MODIS shows a slight advantage from stronger diurnal constraints on rapidly varying smoke plumes. Both experiments underestimate peak AOD during wildfires (stemming from the ∼50 km grid artificially diluting concentrated smoke) and in African mixed-aerosol highlands (driven by topographic smoothing). Overall, VIIRS observational density compensates for reduced temporal sampling, supporting a reliable transition for GEOS aerosol forecasting and reanalyses.