Modeling atmospheric brown carbon in the GISS ModelE Earth system model

Brown carbon (BrC) is an absorbing organic aerosol (OA), primarily emitted through biomass burning (BB), which exhibits light absorption unique to both black carbon (BC) and other organic aerosols. Despite many field and laboratory studies seeking to constrain BrC properties, the radiative forcing (...

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Main Authors: DeLessio, Maegan A., Tsigaridis, Kostas, Bauer, Susanne E., Chowdhary, Jacek, Schuster, Gregory L.
Format: Text
Language:English
Published: 2024
Subjects:
Online Access:https://doi.org/10.5194/egusphere-2023-2472
https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2472/
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spelling ftcopernicus:oai:publications.copernicus.org:egusphere115614 2024-09-15T17:35:14+00:00 Modeling atmospheric brown carbon in the GISS ModelE Earth system model DeLessio, Maegan A. Tsigaridis, Kostas Bauer, Susanne E. Chowdhary, Jacek Schuster, Gregory L. 2024-05-29 application/pdf https://doi.org/10.5194/egusphere-2023-2472 https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2472/ eng eng doi:10.5194/egusphere-2023-2472 https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2472/ eISSN: Text 2024 ftcopernicus https://doi.org/10.5194/egusphere-2023-2472 2024-08-28T05:24:15Z Brown carbon (BrC) is an absorbing organic aerosol (OA), primarily emitted through biomass burning (BB), which exhibits light absorption unique to both black carbon (BC) and other organic aerosols. Despite many field and laboratory studies seeking to constrain BrC properties, the radiative forcing (RF) of BrC is still highly uncertain. To better understand its climate impact, we introduced BrC to the One-Moment Aerosol (OMA) module of the GISS ModelE Earth system model (ESM). We assessed ModelE sensitivity to primary BrC processed through a novel chemical aging scheme and to secondary BrC formed from biogenic volatile organic compounds (BVOCs). Initial results show that BrC typically contributes a top-of-the-atmosphere (TOA) radiative effect of 0.04 W m −2 . Sensitivity tests indicate that explicitly simulating BrC (separating it from other OAs), including secondary BrC, and simulating chemical bleaching of BrC contribute distinguishable radiative effects and should be accounted for in BrC schemes. This addition of prognostic BrC to ModelE allows greater physical and chemical complexity in OA representation with no apparent trade-off in model performance, as the evaluation of ModelE aerosol optical depth against Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) retrieval data, with and without the BrC scheme, reveals similar skill in both cases. Thus, BrC should be explicitly simulated to allow more physically based chemical composition, which is crucial for more detailed OA studies like comparisons to in situ measurement campaigns. We include a summary of best practices for BrC representation within ModelE at the end of this paper. Text Aerosol Robotic Network Copernicus Publications: E-Journals
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description Brown carbon (BrC) is an absorbing organic aerosol (OA), primarily emitted through biomass burning (BB), which exhibits light absorption unique to both black carbon (BC) and other organic aerosols. Despite many field and laboratory studies seeking to constrain BrC properties, the radiative forcing (RF) of BrC is still highly uncertain. To better understand its climate impact, we introduced BrC to the One-Moment Aerosol (OMA) module of the GISS ModelE Earth system model (ESM). We assessed ModelE sensitivity to primary BrC processed through a novel chemical aging scheme and to secondary BrC formed from biogenic volatile organic compounds (BVOCs). Initial results show that BrC typically contributes a top-of-the-atmosphere (TOA) radiative effect of 0.04 W m −2 . Sensitivity tests indicate that explicitly simulating BrC (separating it from other OAs), including secondary BrC, and simulating chemical bleaching of BrC contribute distinguishable radiative effects and should be accounted for in BrC schemes. This addition of prognostic BrC to ModelE allows greater physical and chemical complexity in OA representation with no apparent trade-off in model performance, as the evaluation of ModelE aerosol optical depth against Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) retrieval data, with and without the BrC scheme, reveals similar skill in both cases. Thus, BrC should be explicitly simulated to allow more physically based chemical composition, which is crucial for more detailed OA studies like comparisons to in situ measurement campaigns. We include a summary of best practices for BrC representation within ModelE at the end of this paper.
format Text
author DeLessio, Maegan A.
Tsigaridis, Kostas
Bauer, Susanne E.
Chowdhary, Jacek
Schuster, Gregory L.
spellingShingle DeLessio, Maegan A.
Tsigaridis, Kostas
Bauer, Susanne E.
Chowdhary, Jacek
Schuster, Gregory L.
Modeling atmospheric brown carbon in the GISS ModelE Earth system model
author_facet DeLessio, Maegan A.
Tsigaridis, Kostas
Bauer, Susanne E.
Chowdhary, Jacek
Schuster, Gregory L.
author_sort DeLessio, Maegan A.
title Modeling atmospheric brown carbon in the GISS ModelE Earth system model
title_short Modeling atmospheric brown carbon in the GISS ModelE Earth system model
title_full Modeling atmospheric brown carbon in the GISS ModelE Earth system model
title_fullStr Modeling atmospheric brown carbon in the GISS ModelE Earth system model
title_full_unstemmed Modeling atmospheric brown carbon in the GISS ModelE Earth system model
title_sort modeling atmospheric brown carbon in the giss modele earth system model
publishDate 2024
url https://doi.org/10.5194/egusphere-2023-2472
https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2472/
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source eISSN:
op_relation doi:10.5194/egusphere-2023-2472
https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2472/
op_doi https://doi.org/10.5194/egusphere-2023-2472
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