Atmospheric Composition Modeling and Analysis Program

May, A.A., et al. (2015), Observations and analysis of organic aerosol evolution in some prescribed fire smoke plumes, Atmos. Chem. Phys., 15, 6323-6335, doi:10.5194/acp-15-6323-2015.

Collier, S., et al. (2016), Regional Influence of Aerosol Emissions from Wildfires Driven by Combustion Efficiency: Insights from the BBOP Campaign, Environ. Sci. Technol., 50, 8613-8622, doi:10.1021/acs.est.6b01617.

Neely, R.R., et al. (2014), Biases in southern hemisphere climate trends induced by coarsely specifying the temporal resolution of stratospheric ozone, Geophys. Res. Lett., 41, doi:10.1002/2014GL061627.

Young, P.J., et al. (2014), Modeling the climate impact of Southern Hemisphere ozone depletion: The importance of the ozone data set, Geophys. Res. Lett., 41, 9033-9039, doi:10.1002/2014GL061738.

Matthes, K., et al. (2017), Solar forcing for CMIP6 (v3.2), Geosci. Model. Dev., 10, 2247-2302, doi:10.5194/gmd-10-2247-2017.

Jackman, C.H., et al. (2016), Atmospheric changes caused by galactic cosmic rays over the period 1960–2010, Atmos. Chem. Phys., 16, 5853-5866, doi:10.5194/acp-16-5853-2016.

Li, C., et al. (2017), New-generation NASA Aura Ozone Monitoring Instrument (OMI) volcanic SO2 dataset: algorithm description, initial results, and continuation with the Suomi-NPP Ozone Mapping and Profiler Suite (OMPS), Atmos. Meas. Tech., 10, 445-458, doi:10.5194/amt-10-445-2017.

Lorente, A., et al. (2017), Structural uncertainty in air mass factor calculation for NO2 and HCHO satellite retrievals, Atmos. Meas. Tech., 10, 759-782, doi:10.5194/amt-10-759-2017.

Zhang, Y., et al. (2017), Continuation of long-term global SO2 pollution monitoring from OMI to OMPS, Atmos. Meas. Tech., 10, 1495-1509, doi:10.5194/amt-10-1495-2017.