Radiative Effect and Climate Impacts of Brown Carbon with the Community Atmosphere Model (CAM5)
Abstract
A recent development in the representation of aerosols in climate models is the realization that some components of organic aerosol (OA), emitted from biomass and biofuel burning, can have a significant contribution to shortwave radiation absorption in the atmosphere. The absorbing fraction of OA is referred to as brown carbon (BrC). This study introduces one of the first implementations of BrC into the Community Atmosphere Model version 5 (CAM5), using a parameterization for BrC absorptivity described in Saleh et al. (2014). Nine-year experiments are run (2003–2011) with prescribed emissions and sea surface temperatures to analyze the effect of BrC in the atmosphere. Model validation is conducted via model comparison to single-scatter albedo and aerosol optical depth from the Aerosol Robotic Network (AERONET). This comparison reveals a model underestimation of single scattering albedo (SSA) in biomass burning regions for both default and BrC model runs, while a comparison between AERONET and the model absorption Ångström exponent shows a marked improvement with BrC implementation. Global annual average radiative effects are calculated due to aerosol–radiation interaction (REari; 0.13 ± 0.01W m-2) and aerosol–cloud interaction (REaci; 0.01 ± 0.04W m-2). REari is similar to other studies’ estimations of BrC direct radiative effect, while REacimore »
- Authors:
-
- Univ. of Wyoming, Laramie, WY (United States). Dept. of Atmospheric Science
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Nanjing Univ. (China). Institute for Climate and Global Change Research, School of Atmospheric Sciences
- Univ. of Wyoming, Laramie, WY (United States). Dept. of Atmospheric Science; Chinese Academy of Sciences (CAS), Beijing (China). International Center for Climate and Environmental Sciences, Inst. of Atmospheric Physics
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
- Sponsoring Org.:
- USDOE Office of Science (SC); USEPA; National Science Foundation (NSF); USDA
- OSTI Identifier:
- 1544233
- Grant/Contract Number:
- 83588301
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Atmospheric Chemistry and Physics Discussions (Online)
- Additional Journal Information:
- Journal Name: Atmospheric Chemistry and Physics Discussions (Online); Journal Volume: 18; Journal Issue: 24; Journal ID: ISSN 1680-7375
- Publisher:
- European Geosciences Union
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES
Citation Formats
Brown, Hunter, Liu, Xiaohong, Feng, Yan, Jiang, Yiquan, Wu, Mingxuan, Lu, Zheng, Wu, Chenglai, Murphy, Shane, and Pokhrel, Rudra. Radiative Effect and Climate Impacts of Brown Carbon with the Community Atmosphere Model (CAM5). United States: N. p., 2018.
Web. doi:10.5194/acp-2018-676.
Brown, Hunter, Liu, Xiaohong, Feng, Yan, Jiang, Yiquan, Wu, Mingxuan, Lu, Zheng, Wu, Chenglai, Murphy, Shane, & Pokhrel, Rudra. Radiative Effect and Climate Impacts of Brown Carbon with the Community Atmosphere Model (CAM5). United States. https://doi.org/10.5194/acp-2018-676
Brown, Hunter, Liu, Xiaohong, Feng, Yan, Jiang, Yiquan, Wu, Mingxuan, Lu, Zheng, Wu, Chenglai, Murphy, Shane, and Pokhrel, Rudra. Fri .
"Radiative Effect and Climate Impacts of Brown Carbon with the Community Atmosphere Model (CAM5)". United States. https://doi.org/10.5194/acp-2018-676. https://www.osti.gov/servlets/purl/1544233.
@article{osti_1544233,
title = {Radiative Effect and Climate Impacts of Brown Carbon with the Community Atmosphere Model (CAM5)},
author = {Brown, Hunter and Liu, Xiaohong and Feng, Yan and Jiang, Yiquan and Wu, Mingxuan and Lu, Zheng and Wu, Chenglai and Murphy, Shane and Pokhrel, Rudra},
abstractNote = {A recent development in the representation of aerosols in climate models is the realization that some components of organic aerosol (OA), emitted from biomass and biofuel burning, can have a significant contribution to shortwave radiation absorption in the atmosphere. The absorbing fraction of OA is referred to as brown carbon (BrC). This study introduces one of the first implementations of BrC into the Community Atmosphere Model version 5 (CAM5), using a parameterization for BrC absorptivity described in Saleh et al. (2014). Nine-year experiments are run (2003–2011) with prescribed emissions and sea surface temperatures to analyze the effect of BrC in the atmosphere. Model validation is conducted via model comparison to single-scatter albedo and aerosol optical depth from the Aerosol Robotic Network (AERONET). This comparison reveals a model underestimation of single scattering albedo (SSA) in biomass burning regions for both default and BrC model runs, while a comparison between AERONET and the model absorption Ångström exponent shows a marked improvement with BrC implementation. Global annual average radiative effects are calculated due to aerosol–radiation interaction (REari; 0.13 ± 0.01W m-2) and aerosol–cloud interaction (REaci; 0.01 ± 0.04W m-2). REari is similar to other studies’ estimations of BrC direct radiative effect, while REaci indicates a global reduction in low clouds due to the BrC semidirect effect. The mechanisms for these physical changes are investigated and found to correspond with changes in global circulation patterns. Comparisons of BrC implementation approaches find that this implementation predicts a lower BrC REari in the Arctic regions than previous studies with CAM5. Implementation of BrC bleaching effect shows a significant reduction in REari (0.06 ± 0.008 W m-2). Also, variations in OA density can lead to differences in REari and REaci, indicating the importance of specifying this property when estimating the BrC radiative effects and when comparing similar studies.},
doi = {10.5194/acp-2018-676},
journal = {Atmospheric Chemistry and Physics Discussions (Online)},
number = 24,
volume = 18,
place = {United States},
year = {Fri Dec 14 00:00:00 EST 2018},
month = {Fri Dec 14 00:00:00 EST 2018}
}
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