The thermal infrared optical depth of mineral dust retrieved from integrated CALIOP and IIR observations

Recent studies have suggested that global climate models tend to underestimate dust particle size in particular, the very coarse mode, leading an underestimated direct radiative effect (DRE) of longwave (LW) thermal infrared (TIR) region. However, magnitude LW DRE remains highly uncertain, because limited observations optical depth at TIR (DAODTIR). This study presents a simple approach retrieve DAODTIR over oceans during nighttime through synergistic use from Infrared Imaging Radiometer (IIR) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), both onboard Pathfinder Satellite Observations (CALIPSO) mission. For each cloud-free dust-laden profile identified by IIR-CALIOP observation, Lookup-Table (LUT) 10.6 μm IIR band brightness temperatures (BT) difference (dBT) under different respect their dust-free BTs is constructed based on CALIOP retrieved vertical priori scattering properties using fast transfer model. Then projecting IIR-observed dBT LUT. Sensitivity show retrieval more susceptible distribution (PSD) assumption than refractive indices. To estimate uncertainty caused PSD assumption, two products, one AERONET Cape Verde other situ measured recent Fennec campaign, are provided. The mainly contributed BT between observation simulation auxiliary atmospheric data. climatology 2013 2019 shows reasonable spatiotemporal variations global-averaged value 0.008 0.013 pre-assumed PSDs. Climatological results agree reasonably well independent products Atmospheric Sounding Interferometer (IASI) active transport regions, such as North Tropical Atlantic (r = 0.9 r 0.8) Indian Ocean 0.8). seasonal interannual variation also well-compared 0.76) coarse-mode AOD 97 selected sites. synergic allows directly compare extrapolated DAOD visible (i.e., 532 nm), which helps evaluate observational constraints DAODTIR. Our clearly reveals much less various uncertainties converted CALIOP. It offers unique prospect collocated lidar passive IR for retrieving