TEMPO Aerosol Optical Depth and Aerosol Layer Height Retrieval Algorithm

Abstract

We developed an aerosol optical depth (AOD) and aerosol layer height (ALH) retrieval algorithm for Tropospheric Emissions: Monitoring of Pollution (TEMPO), the first geostationary sensor for monitoring air pollution over North America by enhancing state-of-the-art algorithms originally developed for polar-orbiting satellites to generate a suite of aerosol products. Specifically, the AOD retrieval is adapted from Visible Infrared Imaging Radiometer Suite retrieval algorithm using blue and red bands, and ALH retrieval is adapted from Tropospheric Monitoring Instrument algorithm using O₂B band. Analysis of initial results indicated that TEMPO top of the atmosphere (TOA) reflectances have positive biases across different wavelengths. Therefore, we developed a soft calibration by deriving regression relationships calculated TOA reflectance with measured TOA reflectance over the ocean. The retrieved AOD and ALH show significant improvements compared to those without soft calibration, particularly over water. Compared to AErosol RObotic NETwork AOD, the retrieved TEMPO AOD has a correlation of 0.83, a bias of −0.01 and a root-mean-squared-error (RMSE) of 0.10 over land, and a correlation of 0.90, a bias of −0.05, and an RMSE of 0.08 over water. The ALH retrievals are compared against measurements from the High Spectral Resolution Lidar 2, which show a bias of 0.14 km, an RMSE of 1.19 km over land and a bias of −1.12 km, an RMSE of 1.25 km over water. Simultaneous retrieval of AOD and ALH is critical to estimate surface concentrations of fine particulate matter to monitor and forecast air quality.