Variational Bias Correction of VIIRS Aerosol Optical Depth in the JEDI-Based Global Data Assimilation System

Aerosol Optical Depth (AOD) retrievals from the Visible Infrared Imaging Radiometer Suite (VIIRS) instruments onboard the S-NPP and JPSS satellites are assimilated into a three-dimensional variational global data assimilation system based on the Joint Effort for Data assimilation Integration (JEDI) framework for the global aerosol forecast system, which is a component of the Unified Forecast System (UFS) at the National Centers for Environmental Prediction (NCEP). Studies have estimated bias in VIIRS AOD data, which appear to be dependent on AOD value and varying over land and ocean. To address these biases and maximize the potential benefit of satellite AOD observations during data assimilation, this work incorporates the variational bias correction (VarBC) of VIIRS AOD within the global aerosol data assimilation system. Various bias models will be investigated, using predictors such as retrieved AOD value, satellite scanning information, constant bias, et al. As an anchor for the VarBC of VIIRS AOD, the Aerosol Robotic Network (AERONET) AOD retrievals are also assimilated. The impact of variational AOD bias correction will be explored through comprehensive validation against various AOD retrievals and analyses. By refining the satellite AOD data assimilation, this research aims to enhance the accuracy of global aerosol analysis and forecast.