Aerosol Detection from the Cloud–Aerosol Transport System on the International Space Station: Algorithm Overview and Implications for Diurnal Sampling

Autor: Edward P. Nowottnick, Kenneth E. Christian, John E. Yorks, Matthew J. McGill, Natalie Midzak, Patrick A. Selmer, Zhendong Lu, Jun Wang, Santo V. Salinas
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Atmosphere, Vol 13, Iss 9, p 1439 (2022)
Druh dokumentu: article
ISSN: 2073-4433
DOI: 10.3390/atmos13091439
Popis: Concentrations of particulate aerosols and their vertical placement in the atmosphere determine their interaction with the Earth system and their impact on air quality. Space-based lidar, such as the Cloud–Aerosol Transport System (CATS) technology demonstration instrument, is well-suited for determining the vertical structure of these aerosols and their diurnal cycle. Through the implementation of aerosol-typing algorithms, vertical layers of aerosols are assigned a type, such as marine, dust, and smoke, and a corresponding extinction-to-backscatter (lidar) ratio. With updates to the previous aerosol-typing algorithms, we find that CATS, even as a technology demonstration, observed the documented seasonal cycle of aerosols, comparing favorably with the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) space-based lidar and the NASA Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) model reanalysis. By leveraging the unique orbit of the International Space Station, we find that CATS can additionally resolve the diurnal cycle of aerosol altitude as observed by ground-based instruments over the Maritime Continent of Southeast Asia.
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