Polarimetric Aerosol and Cloud Remote Sensing Inversion - AirMSPI Practice and Beyond
Aerosols and their interactions with clouds are the major uncertainty sources of climate forcing. A polarimeter that measures both radiance and polarization of scattered light has been proved to be highly valuable to improve the remote sensing accuracy of aerosol/cloud optical and microphysical properties. The last few decades have seen significant development of forward and inverse remote sensing models for inferring aerosol and cloud properties from polarimetry. In this talk, I will 1) introduce my recent progress on algorithm development for polarimetric remote sensing of aerosols, clouds, water vapor, and surface properties, with application to JPL’s airborne polarimeter - Multiangle SpectroPolarimetric Imager (AirMSPI) and to Earth Venture Instrument - Multi-Angle Imager for Aerosols (MAIA); 2) demonstrate the observation of cloudbow shift from a single polarimetric image of stratocumulus clouds and estimate of cloud-top droplet size distribution at pixel-scale; 3) discuss the benefits of using real multi-angle polarimetric measurements to constrain aerosol properties and the optimal location of view angles for aerosol characterization; 4) demonstrate the combined use of lidar and polarimetric measurements in field campaign to resolve the vertical profiles of aerosol abundance, size distribution, refractive index and nonsphericity; and 5) introduce our new efforts on the formulating an correlation-based inversion method for aerosol property (CIMAP) retrieval that incorporates a new constraint, correlations in particle properties, into optimization to enhance the inversion efficiency and accuracy and into radiative transfer calculation to improve the modeling efficiency for high spatial-resolution radiometric or polarimetric imaging. CIMAP retrievals will be demonstrated using AirMSPI and AERONET measurements.
Bio: Dr. Feng Xu is an associate professor with the School of Meteorology at the University of Oklahoma (OU). His research interests include atmospheric remote sensing inversion, radiative transfer modeling and light scattering by small particles. He developed Level-2 aerosol retrieval prototype algorithm for NASA's EVI Instrument – Multi-Angle Imager for Aerosols. Before joining OU, he worked at the Jet Propulsion Laboratory (JPL) and developed research algorithms for the Airborne Multiangle SpectroPolarimetric Imager to retrieve aerosol and cloud properties. Working as a member of the Algorithm Working Group of NASA ATMOS in Pre-phase A (formerly, ACCP), he developed a combined lidar and polarimeter research inversion algorithm to assess the uncertainties of ACCP specified aerosol geophysical variables and to retrieve aerosol properties from measurements such as those acquired by GISS Research Scanning Polarimeter and Langley High Spectral Resolution Lidar 2. Dr. Xu also serves as an editor of JAS and associate editor of JQSRT and Front. Remote Sens.