Nighttime smoke aerosol optical depth over U.S. rural areas: first retrieval from VIIRS moonlight observations

An algorithm for retrieving nighttime aerosol optical depth (AOD) from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB) observations of reflected moonlight is presented for the rural areas during the western U.S. fire seasons. The algorithm uses the UNified and Linearized Radiative Transfer Model (UNL-RTM) with newly developed capabilities considering lunar illuminations. Cloud and fire pixels are screened out by utilizing the radiance from the VIIRS Moderate-resolution Bands (M-band) and the DNB. Rural and city pixels are classified based on a pre-calculated city light database. The surface spectral reflectance for DNB ranging from 500 to 900 nm is estimated by a random forest approach which is trained using the surface spectral reflectance from the existing spectral libraries. For the fire seasons of 2017 and 2020, the nighttime AOD retrieval is shown to provide indispensable role to describe the nonlinear diurnal movement of smoke transport and discern the source of smoke plumes heretofore observable only in the daytime. The retrieved AOD values show good agreements with spatiotemporally collocated AERONET and CALIOP AOD values, with linear correlation coefficient values of ~0.95 and ~86% of the AOD pairs falling in an uncertainty envelope of (0.085 + 0.10AOD), which is superior to AOD reanalysis from MERRA-2. These results affirm the significant potential of nighttime AOD to improve analysis and forecast of regional to global biomass-burning aerosol distributions, filling a critical gap in the diurnal description of a critical element in Earths climate system.