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Assessment of Dust Size Retrievals Based on AERONET: A Case Study of Radiative Closure From Visible‐Near‐ Infrared to Thermal Infrared
Title: Assessment of Dust Size Retrievals Based on AERONET: A Case Study of Radiative Closure From Visible‐Near‐ Infrared to Thermal Infrared
Authors: Zheng, JianyuZhang, ZhiboDeSouza-Machado, SergioRyder, Claire L.Garnier, AnneDi Mauro, BiagioYang, PingWelton, Ellsworth J.Yu, HongbinBarreto Velasco, África ORCID RESEARCHERID SCOPUSID Autor AEMETYela González, Margarita
Keywords: Dust particles; Climate impacts; VIS-NIR; AERONET
Issue Date: 2024
Publisher: Wiley Open Access; American Geophysical Union
Citation: Geophysical Research Letters. 2024, 51(4), e2023GL106808
Publisher version:
Abstract: Super-coarse dust particles (diameters >10 μm) are evidenced to be more abundant in the atmosphere than model estimates and contribute significantly to the dust climate impacts. Since super-coarse dust accounts for less dust extinction in the visible-to-near-infrared (VIS-NIR) than in the thermal infrared (TIR) spectral regime, they are suspected to be underestimated by remote sensing instruments operates only in VIS-NIR, including Aerosol Robotic Networks (AERONET), a widely used data set for dust model validation. In this study, we perform a radiative closure assessment using the AERONET-retrieved size distribution in comparison with the collocated Atmospheric Infrared Sounder (AIRS) TIR observations with comprehensive uncertainty analysis. The consistently warm bias in the comparisons suggests a potential underestimation of super-coarse dust in the AERONET retrievals due to the limited VIS-NIR sensitivity. An extra super-coarse mode included in the AERONET-retrieved size distribution helps improve the TIR closure without deteriorating the retrieval accuracy in the VIS-NIR.
Sponsorship : J. Zheng, Z. Zhang and A. Garnier are supported by a NASA grant (no. 80NSSC20K0130) from the CALIPSO and CloudSat program managed by David Considine. Z. Zhang also acknowledges funding support from the NSF (AGS-2232138). H. Yu was supported by the CloudSat/CALIPSO program. C. L. Ryder acknowledges funding from NERC IRF Grant NE/M018288/1. The computations in this study were performed at the UMBC High Performance Computing Facility (HPCF). The facility is supported by the US National Science Foundation through the MRI program (Grants CNS-0821258 and CNS-1228778) and the SCREMS program (Grant DMS-0821311), with substantial support from UMBC. We thank NASA for providing the AIRS, CLIMCAPS and MODIS data, which are publicly available at and
ISSN: 0094-8276
Appears in Collections:Artículos científicos 2023-2026

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