Polarimetric Aerosol and Cloud Remote Sensing: from AirMSPI to MAIA
Aerosols and clouds are two major uncertainty sources in estimating global climate forcing. Aerosols also impact the environment and human health. To better characterize their effects and to understand their interactions, the 2017 Decadal Survey (DS) defines aerosols and clouds as two “designated observables”. As a cutting-edge remote sensing technology, a polarimeter that measures both radiance and polarization of scattered light is considered by the DS to improve the remote sensing of aerosol and cloud properties and their spatial distributions. This talk will introduce two polarimeters, the airborne Multiangle SpectroPolarimetric Imager (AirMSPI) and the satellite-borne Multi-Angle Imager for Aerosols (MAIA). Their remote sensing capabilities for aerosol, cloud, water-vapor abundance, and surface properties will be demonstrated. I will a) show observations of cloudbow shift from a single polarimetric image of stratocumulus clouds and estimate of cloud-top droplet size distribution at pixel-scale; b) emphasize the importance of performing simultaneous cloud and above-cloud aerosol retrieval to mitigate their cross-contamination; and c) demonstrate the benefits of using multi-angle and polarimetric measurements to constrain aerosol/cloud properties. I will also introduce the remote sensing algorithms that combine the strengths of multi-angle polarimetry, polarized radiative transfer models and a priori constraints on correlations in particle properties that vary in spatial and temporal scales.
Dr. Feng Xu is a research scientist at the Jet Propulsion Laboratory, California Institute of Technology. His research focuses on developing and applying remote sensing theory for passive aerosol and cloud remote sensing. As a science team member on NASA EVI mission – Multi-Angle Imager for Aerosols (MAIA), he leads the development of MAIA Level-2 aerosol retrieval algorithm. He is also responsible for developing aerosol and cloud remote sensing algorithms for MAIA’s prototype – AirMSPI.