Journal article
First lunar-light mapping of nighttime dust season oceanic aerosol optical depth over North Atlantic from space
Remote sensing of environment, Vol.312, 114315
10/01/2024
DOI: 10.1016/j.rse.2024.114315
Abstract
This paper presents the Nighttime Ocean Aerosol Optical Depth (AOD) Retrieval Algorithm (NOARA), an innovative method for deriving the oceanic AOD from the reflected moonlight observation of Day-Night Band (DNB) aboard the Visible Infrared Imaging Radiometer Suite (VIIRS) over ocean surfaces. Building upon the recent development of nighttime AOD retrievals for rural/wild areas over land, the NOARA introduces several advancements tailored for oceanic application: (a) the new dust and sea salt optical property models based on the AERONET observation; (b) the Cox-Munk bidirectional reflectance distribution function (BRDF) model that better represents the ocean surface reflectance; (c) the new internal cloud and dust masking schemes for the ocean areas. Case studies show that the nighttime AODs are in good consistency with multiple AOD measurements such as from AERONET and CALIOP. The algorithm fills the observational gap for a comprehensive understanding of the diurnal cycle of the dust transport over the ocean and has the potential to provide vital information to better constrain the chemical transport model.
•First nighttime oceanic AOD retrieval algorithm from VIIRS lunar observation.•AOD retrievals agree well with the nighttime AERONET and CALIOP observations.•Day/night AOD together enable more coherent monitoring of the Sahara dust transport.•Assimilation of daytime AOD is insufficient to constrain dust transport in CTM.•Nighttime oceanic AOD provides insights on the evolution of diurnal dust transport.
Details
- Title: Subtitle
- First lunar-light mapping of nighttime dust season oceanic aerosol optical depth over North Atlantic from space
- Creators
- Meng Zhou - Interdisciplinary Graduate Program in Geo-Informatics, The University of Iowa, Iowa City, IA 52242, USAJun Wang - Interdisciplinary Graduate Program in Geo-Informatics, The University of Iowa, Iowa City, IA 52242, USAXi Chen - University of Iowa, Iowa Technology InstituteYi Wang - University of IowaPeter R. Colarco - Goddard Space Flight CenterRobert C. Levy - Goddard Space Flight CenterSteven D. Miller - Colorado State University
- Resource Type
- Journal article
- Publication Details
- Remote sensing of environment, Vol.312, 114315
- Publisher
- Elsevier Inc
- DOI
- 10.1016/j.rse.2024.114315
- ISSN
- 0034-4257
- eISSN
- 1879-0704
- Grant note
- NASA SNPP/JPSS/Terra/Aqua program: 80NNSC21K1976, 80NSSC21K1981 Future Investigators in NASA Earth and Space Science and Technology (FINESST) program: 80NSSC21K1628
This study was supported by NASA SNPP/JPSS/Terra/Aqua program (grant #: 80NNSC21K1976 and 80NSSC21K1981). Meng Zhou is supported by the support of Future Investigators in NASA Earth and Space Science and Technology (FINESST) program (grant #: 80NSSC21K1628). We express our gratitude for the open access to VIIRS data, provided by NASA's Earth Observing System Data and Information System (EOSDIS), as well as the CALIOP Level 2 aerosol profile data from NASA Langley Research Center's Atmospheric Science Data Center. Our appreciation extends to all Principal Investigators, Co-Principal Investigators, and respective team members for their efforts in setting up and maintaining the AERONET sites integral to this research. We also acknowledge atmospheric data and services center (AERIS) for their efforts to maintain the IASI dust AOD retrieval.
- Language
- English
- Date published
- 10/01/2024
- Academic Unit
- Electrical and Computer Engineering; Chemical and Biochemical Engineering; Iowa Technology Institute; Civil and Environmental Engineering; Physics and Astronomy
- Record Identifier
- 9984693978402771
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