@Article{Ogunro_Atmos_20180512,
 author		= {Oluwaseun O. Ogunro and Scott M. Elliott and Oliver W. Wingenter and Clara Deal and Weiwei Fu and Nathan Collier and Forrest M. Hoffman},
 title		= {Evaluating Uncertainties in Marine Biogeochemical Models: Benchmarking Aerosol Precursors},
 journal	= Atmos,
 volume		= 9,
 number		= 5,
 doi		= {10.3390/atmos9050184},
 day		= 12,
 month		= may,
 year		= 2018,
 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.}
}