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

Edward P. Nowottnick; Kenneth E. Christian; John E. Yorks; Matthew J. McGill; Natalie Midzak; Patrick A. Selmer; Zhendong Lu; Jun Wang; Santo V. Salinas

doi:10.3390/atmos13091439

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

Journal article

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Peer reviewed

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

Edward P. Nowottnick, Kenneth E. Christian, John E. Yorks, Matthew J. McGill, Natalie Midzak, Patrick A. Selmer, Zhendong Lu, Jun Wang and Santo V. Salinas

Atmosphere, Vol.13(1439), p.1439

09/01/2022

DOI: 10.3390/atmos13091439

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Abstract

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.

Lidar

aerosol

algorithm

diurnal cycle

seasonal

Details

Title: Subtitle: Aerosol Detection from the Cloud–Aerosol Transport System on the International Space Station: Algorithm Overview and Implications for Diurnal Sampling
Creators: Edward P. Nowottnick - Goddard Space Flight Center
Kenneth E. Christian - University of Maryland, College Park
John E. Yorks - Goddard Space Flight Center
Matthew J. McGill - University of Iowa
Natalie Midzak - University of North Dakota
Patrick A. Selmer - Science Systems and Applications (United States)
Zhendong Lu - Department of Chemical and Biochemical Engineering, The University of Iowa, Iowa City, IA 52242, USA
Jun Wang - University of Iowa
Santo V. Salinas - Centre for Remote Imaging, Sensing and Processing (CRISP), National University of Singapore, Singapore 119076, Singapore
Resource Type: Journal article
Publication Details: Atmosphere, Vol.13(1439), p.1439
DOI: 10.3390/atmos13091439
eISSN: 2073-4433
Publisher: MDPI AG
Language: English
Date published: 09/01/2022
Academic Unit: Civil and Environmental Engineering; Iowa Technology Institute; Physics and Astronomy; Chemical and Biochemical Engineering
Record Identifier: 9984297558602771

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