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

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

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Autores principales:	Hailing Jia, Xiaoyan Ma, Fangqun Yu, Johannes Quaas
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/50aa45ec7aba43548249ab39623a7bca
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spelling	oai:doaj.org-article:50aa45ec7aba43548249ab39623a7bca2021-12-02T17:23:59ZSignificant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods10.1038/s41467-021-23888-12041-1723https://doaj.org/article/50aa45ec7aba43548249ab39623a7bca2021-06-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-23888-1https://doaj.org/toc/2041-1723Satellite-based estimates of radiative forcing by aerosol–cloud interactions are consistently smaller than those from global models, hampering accurate projections of future climate change. Here, the authors show that the discrepancy can be substantially reduced by correcting sampling biases induced by inherent limitations of satellite measurements.Hailing JiaXiaoyan MaFangqun YuJohannes QuaasNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Hailing Jia Xiaoyan Ma Fangqun Yu Johannes Quaas Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods
description	Satellite-based estimates of radiative forcing by aerosol–cloud interactions are consistently smaller than those from global models, hampering accurate projections of future climate change. Here, the authors show that the discrepancy can be substantially reduced by correcting sampling biases induced by inherent limitations of satellite measurements.
format	article
author	Hailing Jia Xiaoyan Ma Fangqun Yu Johannes Quaas
author_facet	Hailing Jia Xiaoyan Ma Fangqun Yu Johannes Quaas
author_sort	Hailing Jia
title	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_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_sort	significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/50aa45ec7aba43548249ab39623a7bca
work_keys_str_mv	AT hailingjia significantunderestimationofradiativeforcingbyaerosolcloudinteractionsderivedfromsatellitebasedmethods AT xiaoyanma significantunderestimationofradiativeforcingbyaerosolcloudinteractionsderivedfromsatellitebasedmethods AT fangqunyu significantunderestimationofradiativeforcingbyaerosolcloudinteractionsderivedfromsatellitebasedmethods AT johannesquaas significantunderestimationofradiativeforcingbyaerosolcloudinteractionsderivedfromsatellitebasedmethods
_version_	1718380967626801152

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

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