Near‐cloud aerosol retrieval using machine learning techniques, and implied direct radiative effects

Yang, C. K. ORCID: https://orcid.org/0000-0001-7685-4481, Chiu, J. C. ORCID: https://orcid.org/0000-0002-8951-6913, Marshak, A. ORCID: https://orcid.org/0000-0002-3973-1359, Feingold, G. ORCID: https://orcid.org/0000-0002-0774-2926, Várnai, T. ORCID: https://orcid.org/0000-0002-7419-2522, Wen, G. ORCID: https://orcid.org/0000-0003-2977-4993, Yamaguchi, T. ORCID: https://orcid.org/0000-0001-8059-0757 and Van Leeuwen, P. J. ORCID: https://orcid.org/0000-0003-2325-5340 (2022) Near‐cloud aerosol retrieval using machine learning techniques, and implied direct radiative effects. Geophysical Research Letters, 49 (20). e2022GL098274. ISSN 0094-8276 doi: 10.1029/2022GL098274

Abstract/Summary

There is a lack of satellite-based aerosol retrievals in the vicinity of low-topped clouds, mainly because reflectance from aerosols is overwhelmed by three-dimensional cloud radiative effects. To account for cloud radiative effects on reflectance observations, we develop a Convolutional Neural Network and retrieve aerosol optical depth (AOD) with 100–500 m horizontal resolution for all cloud-free regions regardless of their distances to clouds. The retrieval uncertainty is 0.01 + 5%AOD, and the mean bias is approximately −2%. In an application to satellite observations, aerosol hygroscopic growth due to humidification near clouds enhances AOD by 100% in regions within 1 km of cloud edges. The humidification effect leads to an overall 55% increase in the clear-sky aerosol direct radiative effect. Although this increase is based on a case study, it highlights the importance of aerosol retrievals in near-cloud regions, and the need to incorporate the humidification effect in radiative forcing estimates.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/109109
Identification Number/DOI	10.1029/2022GL098274
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	AGU
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