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Jia H, Ma X, Yu F, Quaas J. Significant underestimation of radiative forcing by aerosol-cloud interactions derived from satellite-based methods. Nat Commun 2021; 12:3649. [PMID: 34131118 PMCID: PMC8206093 DOI: 10.1038/s41467-021-23888-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 05/17/2021] [Indexed: 02/05/2023] Open
Abstract
Satellite-based estimates of radiative forcing by aerosol-cloud interactions (RFaci) 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 RFaci 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 RFaci, the improved one substantially increases (especially over land), resolving a major difference with models.
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Affiliation(s)
- Hailing Jia
- grid.260478.fCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, and Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing, China ,grid.265850.c0000 0001 2151 7947Atmospheric Sciences Research Center, University at Albany, Albany, NY USA ,grid.9647.c0000 0004 7669 9786Institute for Meteorology, Universität Leipzig, Leipzig, Germany
| | - Xiaoyan Ma
- grid.260478.fCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, and Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing, China
| | - Fangqun Yu
- grid.265850.c0000 0001 2151 7947Atmospheric Sciences Research Center, University at Albany, Albany, NY USA
| | - Johannes Quaas
- grid.9647.c0000 0004 7669 9786Institute for Meteorology, Universität Leipzig, Leipzig, Germany
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Aerosol Effective Radiative Forcing in the Online Aerosol Coupled CAS-FGOALS-f3-L Climate Model. ATMOSPHERE 2020. [DOI: 10.3390/atmos11101115] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The effective radiative forcing (ERF) of anthropogenic aerosol can be more representative of the eventual climate response than other radiative forcing. We incorporate aerosol–cloud interaction into the Chinese Academy of Sciences Flexible Global Ocean–Atmosphere–Land System (CAS-FGOALS-f3-L) by coupling an existing aerosol module named the Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) and quantified the ERF and its primary components (i.e., effective radiative forcing of aerosol-radiation interactions (ERFari) and aerosol-cloud interactions (ERFaci)) based on the protocol of current Coupled Model Intercomparison Project phase 6 (CMIP6). The spatial distribution of the shortwave ERFari and ERFaci in CAS-FGOALS-f3-L are comparable with that of most available CMIP6 models. The global mean 2014–1850 shortwave ERFari in CAS-FGOALS-f3-L (−0.27 W m−2) is close to the multi-model means in 4 available models (−0.29 W m−2), whereas the assessing shortwave ERFaci (−1.04 W m−2) and shortwave ERF (−1.36 W m−2) are slightly stronger than the multi-model means, illustrating that the CAS-FGOALS-f3-L can reproduce the aerosol radiation effect reasonably well. However, significant diversity exists in the ERF, especially in the dominated component ERFaci, implying that the uncertainty is still large.
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Mülmenstädt J, Nam C, Salzmann M, Kretzschmar J, L’Ecuyer TS, Lohmann U, Ma PL, Myhre G, Neubauer D, Stier P, Suzuki K, Wang M, Quaas J. Reducing the aerosol forcing uncertainty using observational constraints on warm rain processes. SCIENCE ADVANCES 2020; 6:eaaz6433. [PMID: 32523991 PMCID: PMC7259935 DOI: 10.1126/sciadv.aaz6433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Accepted: 03/30/2020] [Indexed: 06/11/2023]
Abstract
Global climate models (GCMs) disagree with other lines of evidence on the rapid adjustments of cloud cover and liquid water path to anthropogenic aerosols. Attempts to use observations to constrain the parameterizations of cloud processes in GCMs have failed to reduce the disagreement. We propose using observations sensitive to the relevant cloud processes rather than only to the atmospheric state and focusing on process realism in the absence of aerosol perturbations in addition to the process susceptibility to aerosols. We show that process-sensitive observations of precipitation can reduce the uncertainty on GCM estimates of rapid cloud adjustments to aerosols. The feasibility of an observational constraint depends on understanding the precipitation intensity spectrum in both observations and models and also on improving methods to compare the two.
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Affiliation(s)
- Johannes Mülmenstädt
- Institute of Meteorology, Universität Leipzig, Leipzig, Germany
- Atmospheric Sciences & Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Christine Nam
- Institute of Meteorology, Universität Leipzig, Leipzig, Germany
| | - Marc Salzmann
- Institute of Meteorology, Universität Leipzig, Leipzig, Germany
| | - Jan Kretzschmar
- Institute of Meteorology, Universität Leipzig, Leipzig, Germany
| | - Tristan S. L’Ecuyer
- Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Ulrike Lohmann
- Institute of Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland
| | - Po-Lun Ma
- Atmospheric Sciences & Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Gunnar Myhre
- CICERO Center for International Climate Research, Oslo, Norway
| | - David Neubauer
- Institute of Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland
| | - Philip Stier
- Department of Physics, University of Oxford, Oxford, UK
| | - Kentaroh Suzuki
- Atmosphere and Ocean Research Institute, University of Tokyo, Tokyo, Japan
| | - Minghuai Wang
- School of Atmospheric Sciences, Nanjing University, Nanjing, China
| | - Johannes Quaas
- Institute of Meteorology, Universität Leipzig, Leipzig, Germany
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