Publication Abstracts

Mao et al. 2018

Mao, J., A. Carlton, R.C. Cohen, W.H. Brune, S.S. Brown, G.M. Wolfe, J.L. Jimenez, H.O.T. Pye, N. Lee Ng, L. Xu, V.F. McNeill, K. Tsigaridis, B.C. McDonald, C. Warneke, A. Guenther, M.J. Alvarado, J. de Gouw, L.J. Mickley, E.M. Leibensperger, R. Mathur, C.G. Nolte, R.W. Portmann, N. Unger, M. Tosca, and L.W. Horowitz, 2018: Southeast Atmosphere Studies: Learning from model-observation syntheses. Atmos. Chem. Phys., 18, 2615-2651, doi:10.5194/acp-18-2615-2018.

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales.

This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.

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BibTeX Citation

@article{ma09310j,
  author={Mao, J. and Carlton, A. and Cohen, R. C. and Brune, W. H. and Brown, S. S. and Wolfe, G. M. and Jimenez, J. L. and Pye, H. O. T. and Lee Ng, N. and Xu, L. and McNeill, V. F. and Tsigaridis, K. and McDonald, B. C. and Warneke, C. and Guenther, A. and Alvarado, M. J. and de Gouw, J. and Mickley, L. J. and Leibensperger, E. M. and Mathur, R. and Nolte, C. G. and Portmann, R. W. and Unger, N. and Tosca, M. and Horowitz, L. W.},
  title={Southeast Atmosphere Studies: Learning from model-observation syntheses},
  year={2018},
  journal={Atmos. Chem. Phys.},
  volume={18},
  pages={2615--2651},
  doi={10.5194%2Facp-18-2615-2018},
}

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RIS Citation

TY  - JOUR
ID  - ma09310j
AU  - Mao, J.
AU  - Carlton, A.
AU  - Cohen, R. C.
AU  - Brune, W. H.
AU  - Brown, S. S.
AU  - Wolfe, G. M.
AU  - Jimenez, J. L.
AU  - Pye, H. O. T.
AU  - Lee Ng, N.
AU  - Xu, L.
AU  - McNeill, V. F.
AU  - Tsigaridis, K.
AU  - McDonald, B. C.
AU  - Warneke, C.
AU  - Guenther, A.
AU  - Alvarado, M. J.
AU  - de Gouw, J.
AU  - Mickley, L. J.
AU  - Leibensperger, E. M.
AU  - Mathur, R.
AU  - Nolte, C. G.
AU  - Portmann, R. W.
AU  - Unger, N.
AU  - Tosca, M.
AU  - Horowitz, L. W.
PY  - 2018
TI  - Southeast Atmosphere Studies: Learning from model-observation syntheses
JA  - Atmos. Chem. Phys.
VL  - 18
SP  - 2615
EP  - 2651
DO  - 10.5194%2Facp-18-2615-2018
ER  -

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