Harmonizing Aerosol Model Parameters With Retrieval Property Assumptions: Brown Carbon as a Case Study

Abstract Brown carbon (BrC) is an absorbing organic aerosol, primarily emitted through biomass burning (BB), with a large degree of variability in observed chemical and microphysical properties. This makes model representation of the species difficult. Retrievals of BrC from measured radiance fields have the potential to constrain model schemes and improve estimates of BrC radiative effects. We used a retrieval of BrC optical depth and mass from Aerosol Robotic Network (AERONET) sites in BB regions to evaluate GISS ModelE Earth system model (ESM)'s BrC module. We approached this evaluation by comparing BrC properties defined in ModelE with underlying properties prescribed by the AERONET retrieval, and then constrained our scheme to match those assumptions. Our analysis showed that just with this initial harmonization, model bias was decreased, and performance, relative to the retrieval, was improved. This allowed for an estimate of global average BrC radiative effect, 0.03 W m −2 , grounded in the measured radiance fields represented by the retrieval. Through this work, we demonstrate the necessity of harmonizing model scheme parameters with speciated retrieval's assumptions, even if such assumptions are not necessarily more physically correct, to ensure an “apples‐to‐apples” comparison and ultimately improve the estimate of individual aerosol direct effects within a climate model.

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Publication Details

Journal
Journal of Geophysical Research Atmospheres
Published
2025-06-19
DOI
https://doi.org/10.1029/2024jd043040
Primary Topic
Atmospheric chemistry and aerosols
Type
article
Field-Weighted Citation Impact
0.00

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article

Harmonizing Aerosol Model Parameters With Retrieval Property Assumptions: Brown Carbon as a Case Study

Susanne Elizabeth Bauer, Gregory L. Schuster, Maegan A. DeLessio, Kostas Tsigaridis
Journal of Geophysical Research Atmospheres
Atmospheric chemistry and aerosols
article

Harmonizing Aerosol Model Parameters With Retrieval Property Assumptions: Brown Carbon as a Case Study

Susanne Elizabeth Bauer, Gregory L. Schuster, Maegan A. DeLessio, Kostas Tsigaridis
article en

Abstract

Abstract Brown carbon (BrC) is an absorbing organic aerosol, primarily emitted through biomass burning (BB), with a large degree of variability in observed chemical and microphysical properties. This makes model representation of the species difficult. Retrievals of BrC from measured radiance fields have the potential to constrain model schemes and improve estimates of BrC radiative effects. We used a retrieval of BrC optical depth and mass from Aerosol Robotic Network (AERONET) sites in BB regions to evaluate GISS ModelE Earth system model (ESM)'s BrC module. We approached this evaluation by comparing BrC properties defined in ModelE with underlying properties prescribed by the AERONET retrieval, and then constrained our scheme to match those assumptions. Our analysis showed that just with this initial harmonization, model bias was decreased, and performance, relative to the retrieval, was improved. This allowed for an estimate of global average BrC radiative effect, 0.03 W m −2 , grounded in the measured radiance fields represented by the retrieval. Through this work, we demonstrate the necessity of harmonizing model scheme parameters with speciated retrieval's assumptions, even if such assumptions are not necessarily more physically correct, to ensure an “apples‐to‐apples” comparison and ultimately improve the estimate of individual aerosol direct effects within a climate model.

Journal of Geophysical Research AtmospheresVol. 130(12)
Goddard Institute for Space Studies (US), Langley Research Center (US), Columbia University (US)
National Aeronautics and Space Administration, Goddard Institute for Space Studies
Climate action
Openalex Percentile: Top 81%
Atmospheric chemistry and aerosols
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Harmonizing Aerosol Model Parameters With Retrieval Property Assumptions: Brown Carbon as a Case Study — Susanne Elizabeth Bauer, Gregory L. Schuster, et al. · Journal of Geophysical Research Atmospheres (2025) | TGRS Research Map | TGRS