Articles | Volume 16, issue 13
https://doi.org/10.5194/acp-16-8071-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-16-8071-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
04 Jul 2016
Research article |
| 04 Jul 2016
Global fine-mode aerosol radiative effect, as constrained by comprehensive observations
Division of Atmospheric Science, Desert Research Institute, Reno, NV 89512, USA
Jung-Eun Chu
Dept. Atmospheric Sciences, Pusan National University, Busan 46241, South Korea
Yunha Lee
Washington State University, Pullman, WA 99164, USA
Twan van Noije
Royal Netherlands Meteorological Institute, 3730 AE De Bilt, the
Netherlands
Hwayoung Jeoung
National Meteorological Satellite Center, 27803, South Korea
Kyung-Ja Ha
Dept. Atmospheric Sciences, Pusan National University, Busan 46241, South Korea
Marguerite Marks
Dept. Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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- Spectral Deconvolution Algorithm for Global Fine-Mode Aerosol Retrieval in the 1990s Using Dual-Angle Satellite Aerosol Data X. Yan et al. 10.1109/TGRS.2023.3332316
- This is FAST: multivariate Full-permutAtion based Stochastic foresT method—improving the retrieval of fine-mode aerosol microphysical properties with multi-wavelength lidar N. Wang et al. 10.1016/j.rse.2022.113226
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- Assessing California Wintertime Precipitation Responses to Various Climate Drivers R. Allen et al. 10.1029/2019JD031736
- Fine-Mode Aerosol Loading Over a Sub-Sahel Location and Its Relation with the West African Monsoon O. Nwofor et al. 10.1007/s41810-018-0024-6
- A La Niña‐Like Climate Response to South African Biomass Burning Aerosol in CESM Simulations A. Amiri‐Farahani et al. 10.1029/2019JD031832
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- New global aerosol fine-mode fraction data over land derived from MODIS satellite retrievals X. Yan et al. 10.1016/j.envpol.2021.116707
- An Improved Global Land Anthropogenic Aerosol Product Based on Satellite Retrievals From 2008 to 2016 C. Liang et al. 10.1109/LGRS.2020.2991730
- Retrieval of gridded aerosol direct radiative forcing based on multiplatform datasets Y. Wang et al. 10.5194/amt-13-575-2020
- Global vertically resolved aerosol direct radiation effect from three years of CALIOP data using the FORTH radiation transfer model M. Korras-Carraca et al. 10.1016/j.atmosres.2019.03.024
- AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states S. Raj et al. 10.5194/gmd-17-6379-2024
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- Spectral Deconvolution Algorithm for Global Fine-Mode Aerosol Retrieval in the 1990s Using Dual-Angle Satellite Aerosol Data X. Yan et al. 10.1109/TGRS.2023.3332316
- This is FAST: multivariate Full-permutAtion based Stochastic foresT method—improving the retrieval of fine-mode aerosol microphysical properties with multi-wavelength lidar N. Wang et al. 10.1016/j.rse.2022.113226
- An Implicit Air Quality Bias Due to the State of Pristine Aerosol X. Zhao et al. 10.1029/2021EF001979
1 citations as recorded by crossref.
Saved (preprint)
Latest update: 21 Nov 2024
Short summary
Currently, the magnitude of aerosol direct forcing is estimated to range from −0.85 W m−2 to +0.15 W m−2. The uncertainty in estimated aerosol direct forcing is largely due to uncertainties in global aerosol simulation models. We processed a comprehensive suite of observations and developed creative uses of observations to constrain aerosol simulations. The net results are that (i) we reduced the forcing uncertainty and (ii) we showed that the forcing must be less negative than the consensus.
Currently, the magnitude of aerosol direct forcing is estimated to range from −0.85 W m−2 to...
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