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Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods

Satellite-based estimates of radiative forcing by aerosol–cloud interactions (RF(aci)) are consistently smaller than those from global models, hampering accurate projections of future climate change. Here we show that the discrepancy can be substantially reduced by correcting sampling biases induced...

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Detalles Bibliográficos
Autores principales: Jia, Hailing, Ma, Xiaoyan, Yu, Fangqun, Quaas, Johannes
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8206093/
https://www.ncbi.nlm.nih.gov/pubmed/34131118
http://dx.doi.org/10.1038/s41467-021-23888-1
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author Jia, Hailing
Ma, Xiaoyan
Yu, Fangqun
Quaas, Johannes
author_facet Jia, Hailing
Ma, Xiaoyan
Yu, Fangqun
Quaas, Johannes
author_sort Jia, Hailing
collection PubMed
description Satellite-based estimates of radiative forcing by aerosol–cloud interactions (RF(aci)) are consistently smaller than those from global models, hampering accurate projections of future climate change. Here we show that the discrepancy can be substantially reduced by correcting sampling biases induced by inherent limitations of satellite measurements, which tend to artificially discard the clouds with high cloud fraction. Those missed clouds exert a stronger cooling effect, and are more sensitive to aerosol perturbations. By accounting for the sampling biases, the magnitude of RFaci (from −0.38 to −0.59 W m(−2)) increases by 55 % globally (133 % over land and 33 % over ocean). Notably, the RF(aci) further increases to −1.09 W m(−2) when switching total aerosol optical depth (AOD) to fine-mode AOD that is a better proxy for CCN than AOD. In contrast to previous weak satellite-based RF(aci), the improved one substantially increases (especially over land), resolving a major difference with models.
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spelling pubmed-82060932021-07-01 Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods Jia, Hailing Ma, Xiaoyan Yu, Fangqun Quaas, Johannes Nat Commun Article Satellite-based estimates of radiative forcing by aerosol–cloud interactions (RF(aci)) are consistently smaller than those from global models, hampering accurate projections of future climate change. Here we show that the discrepancy can be substantially reduced by correcting sampling biases induced by inherent limitations of satellite measurements, which tend to artificially discard the clouds with high cloud fraction. Those missed clouds exert a stronger cooling effect, and are more sensitive to aerosol perturbations. By accounting for the sampling biases, the magnitude of RFaci (from −0.38 to −0.59 W m(−2)) increases by 55 % globally (133 % over land and 33 % over ocean). Notably, the RF(aci) further increases to −1.09 W m(−2) when switching total aerosol optical depth (AOD) to fine-mode AOD that is a better proxy for CCN than AOD. In contrast to previous weak satellite-based RF(aci), the improved one substantially increases (especially over land), resolving a major difference with models. Nature Publishing Group UK 2021-06-15 /pmc/articles/PMC8206093/ /pubmed/34131118 http://dx.doi.org/10.1038/s41467-021-23888-1 Text en © The Author(s) 2021, corrected publication 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Jia, Hailing
Ma, Xiaoyan
Yu, Fangqun
Quaas, Johannes
Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods
title Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods
title_full Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods
title_fullStr Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods
title_full_unstemmed Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods
title_short Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods
title_sort significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8206093/
https://www.ncbi.nlm.nih.gov/pubmed/34131118
http://dx.doi.org/10.1038/s41467-021-23888-1
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