Improving Aerosol Analysis and Forecast over the Arctic Region with OMI Assimilation

Aerosol mass transport modeling over the Arctic region is challenging. Despite critical advances in global aerosol mass transport modeling, achieved primarily through satellite-based data assimilation, observational limitations have resulted in broad data gaps in Arctic aerosol observations. In this study, we examine the benefit of sequentially assimilating available satellite-based aerosol datasets for generating a three-dimensional Arctic aerosol mass reanalysis product. We evaluate the impact on the Navy Aerosol Analysis and Prediction System (NAAPS) after assimilating MODIS, MISR and a reprocessed CALIOP dataset. MODIS and MISR provide very few retrievals annually over the region, due to high surface albedo from snow and ice-covered surfaces. CALIOP Level 2 algorithms exhibit limited sensitivity in the Arctic from diffuse aerosol structure. Instead, we describe assimilation of a proxy CALIOP Level 2 dataset staged at one-degree along-track resolution. We then present a newly-developed capability for assimilating OMI aerosol index in the Arctic for NAAPS (based on forward modeling via the VLIDORT radiative transfer code) which distinguishes absorbing smoke and dust aerosols over bright regional surfaces.