PhD Proposal: Anthony Bratt
TITLE: Remote Sensing of Aerosol Absorption Using Satellite-Based Lidar and Near-Infrared Spectroscopy
ABSTRACT: Aerosols are a major component of the interaction of incoming sunlight with the Earth. All sunlight interacting with the earth must pass through the atmosphere, and the difficulty in determining the location of aerosols, and quantifying their properties, especially the amount of incident light that they absorb and convert into heat, is a source of great uncertainty in predicting the imbalance of incoming and outgoing electromagnetic radiation. Our ability to reliably predict changes in climate requires reducing our uncertainty in these light-absorbing aerosols. This project attacks this problem using a combination of tools that has not been available before. The Orbiting Carbon Observatory 2 (OCO-2) is a satellite in a polar orbit about the earth that provides nadir-aimed hyperspectral measurements in the oxygen A band. Its spectral resolution in the oxygen A band is superior to past and current satellite instrumentation. The improved resolution better resolves the fine absorption lines in the A band, along which most of the information needed for aerosol absorption lies. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is a venerated active sensing platform that provides excellent satellite-based profiles of aerosols and clouds. OCO-2 and CALIPSO fly in formation with each other, so their measurements can be combined. Using an optimal-estimation configuration of forward and inverse algorithms, it is proposed to retrieve the effective absorption of aerosols in columns of air observed in globally distributed co-located measurements over land, by OCO-2 and CALIOP. The forward algorithm models the spectral radiances in the oxygen A band observed by the OCO-2 instrument, by solving the radiative transfer equation in a plane-parallel atmosphere, in which the CALIOP data constrain the vertical distribution of aerosols. The inverse algorithm searches for aerosol optical thickness and absorption by minimizing the difference between the simulated A band spectrum and the measured A band spectrum. Results will be validated against ground-based Aerosol Robotic Network (AERONET) aerosol inversions. Successful completion of this work will provide a way to quantify the amount of light absorbed by aerosols in the near-infrared oxygen A band. This will add the A band, and the OCO-2 satellite, to the sparse list of tools that can determine aerosol absorption. Additionally, it will demonstrate the usefulness of combining the vertical distribution of aerosols from lidar, with the measurements from the absorption spectrum, and provide a small step in bringing the uncertainty in global radiative forcing under control.