Assessing the benefits of Imaging Infrared Radiometer observations for the CALIOP version 4 cloud and aerosol discrimination algorithm

Abstract. The features detected in monolayer atmospheric columns sounded by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and classified as cloud or aerosol layers CALIOP version 4 (V4) discrimination (CAD) algorithm are reassessed using perfectly collocated brightness temperatures measured Imaging Infrared Radiometer (IIR) aboard same satellite. Using IIR's three wavelength measurements of that confidently CAD algorithm, we calculate two-dimensional (2-D) probability distribution functions (PDFs) IIR temperature differences (BTDs) for different types. We then compare these PDFs 1-D radiative transfer simulations ice water clouds dust marine aerosols. 2-D BTD signature PDFs, develop deploy a new IIR-based classifications obtained to results reported CALIOP-only V4 algorithm. observations shown be able identify good accuracy. identifications agree very well confident (88 %). More importantly, simultaneous use information reduces ambiguity notable fraction “not confident” classifications. 28 % 14 ambiguous reclassified more appropriately through tropics midlatitudes, respectively. relatively little help deriving high-confidence most aerosols, low altitudes small optical depths yield signatures similar those clear skies. However, misclassifications layers, such dense elevated smoke can corrected layer classification including information. 10 %, 16 6 dust, polluted tropospheric smoke, respectively, found misclassified measurements.