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Atmosphere 2018, 9(5), 184; https://doi.org/10.3390/atmos9050184

Evaluating Uncertainties in Marine Biogeochemical Models: Benchmarking Aerosol Precursors

1
Oak Ridge National Laboratory, Climate Change Science Institute (CCSI), Oak Ridge, TN 37831, USA
2
Los Alamos National Laboratory, Los Alamos, NM 87545, USA
3
Chemistry Department, New Mexico Institute of Mining and Technology, Socorro, NM 87801 USA
4
International Arctic Research Center (IARC), University of Alaska, Fairbanks, AK 99775, USA
5
Department of Earth System Science, University of California, Irvine, CA 92697, USA
6
Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, TN 37996, USA
*
Author to whom correspondence should be addressed.
Received: 5 April 2018 / Revised: 2 May 2018 / Accepted: 8 May 2018 / Published: 12 May 2018
(This article belongs to the Special Issue Ocean Contributions to the Marine Boundary Layer Aerosol Budget)
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Abstract

The effort to accurately estimate global radiative forcing has long been hampered by a degree of uncertainty in the tropospheric aerosol contribution. Reducing uncertainty in natural aerosol processes, the baseline of the aerosol budget, thus becomes a fundamental task. The appropriate representation of aerosols in the marine boundary layer (MBL) is essential to reduce uncertainty and provide reliable information on offsets to global warming. We developed an International Ocean Model Benchmarking package to assess marine biogeochemical process representations in Earth System Models (ESMs), and the package was employed to evaluate surface ocean concentrations and the sea–air fluxes of dimethylsulfide (DMS). Model performances were scored based on how well they captured the distribution and variability contained in high-quality observational datasets. Results show that model-data biases increased as DMS enters the MBL, but unfortunately over three-quarters of the models participating in the fifth Coupled Model Intercomparison Project (CMIP5) did not have a dynamic representation of DMS. When it is present, models tend to over-predict sea surface concentrations in the productive region of the eastern tropical Pacific by almost a factor of two, and the sea–air fluxes by a factor of three. Systematic model-data benchmarking as described here will help to identify such deficiencies and subsequently lead to improved subgrid-scale parameterizations and ESM development. View Full-Text
Keywords: biogeochemistry; benchmarking; biogenic volatile organic compounds; dissolved organic carbon; sea-air flux; marine aerosols; earth system modeling biogeochemistry; benchmarking; biogenic volatile organic compounds; dissolved organic carbon; sea-air flux; marine aerosols; earth system modeling
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Ogunro, O.O.; Elliott, S.M.; Wingenter, O.W.; Deal, C.; Fu, W.; Collier, N.; Hoffman, F.M. Evaluating Uncertainties in Marine Biogeochemical Models: Benchmarking Aerosol Precursors. Atmosphere 2018, 9, 184.

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