Constraining Aerosol Vertical Profile in the Boundary Layer Using Hyperspectral Measurements of Oxygen Absorption

• Published in: Geophysical Research Letters
• Main Authors: Zeng, Zhao-Cheng, Natraj, Vijay, Xu, Feng, Pongetti, Thomas J., Shia, Run-Lie, Kort, Eric A., Toon, Geoffrey C., Sander, Stanley P., Yung, Yuk L.
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Geophysical Union 2018
• Subjects: Aerosol Robotic Network
• Online Access: https://authors.library.caltech.edu/90156/; https://authors.library.caltech.edu/90156/3/Zeng_et_al-2018-Geophysical_Research_Letters.pdf; https://authors.library.caltech.edu/90156/2/grl58079-sup-0001-2018gl079286_s01.pdf; https://resolver.caltech.edu/CaltechAUTHORS:20181008-135406047

This study attempts to infer aerosol vertical structure in the urban boundary layer using passive hyperspectral measurements. A spectral sorting technique is developed to retrieve total aerosol optical depth (AOD) and effective aerosol layer height (ALH) from hyperspectral measurements in the 1.27‐μm oxygen absorption band by the mountaintop Fourier Transform Spectrometer at the California Laboratory for Atmospheric Remote Sensing instrument (1,673 m above sea level) overlooking the LA basin. Comparison to AOD measurements from Aerosol Robotic Network and aerosol backscatter profile measurements from a Mini MicroPulse Lidar shows agreement, with coefficients of determination (r^2) of 0.74 for AOD and 0.57 for effective ALH. On average, the AOD retrieval has an error of 24.9% and root‐mean‐square error of 0.013, while the effective ALH retrieval has an error of 7.8% and root‐mean‐square error of 67.01 m. The proposed method can potentially be applied to existing and future satellite missions with hyperspectral oxygen measurements to constrain aerosol vertical distribution on a global scale.