Atmospheric Composition Modeling and Analysis Program

Myhre, G., et al. (2009), Modelled radiative forcing of the direct aerosol effect with multi-observation evaluation, Atmos. Chem. Phys., 9, 1365-1392, doi:10.5194/acp-9-1365-2009.

Kahn, R.A., et al. (2017), SAM-CAAM: A Concept for Acquiring Systematic Aircraft Measurements to Characterize Aerosol Air Masses, Bull. Am. Meteoro. Soc., 2215-2228, doi:10.1175/BAMS-D-16-0003.1.

Li, J., et al. (2016), Reducing multisensor satellite monthly mean aerosol optical depth uncertainty: 1. Objective assessment of current AERONET locations, J. Geophys. Res., 121, doi:10.1002/2016JD025469.

Li, J., et al. (2017), Reducing multisensor monthly mean aerosol optical depth uncertainty: 2. Optimal locations for potential ground observation deployments, J. Geophys. Res., 122, doi:10.1002/2016JD026308.

Vernon, C.J., et al. (2018), The impact of MISR-derived injection height initialization on wildfire and volcanic plume dispersion in the HYSPLIT model, Atmos. Meas. Tech., 11, 6289-6307, doi:10.5194/amt-11-6289-2018.

Kahn, R.A., et al. (2016), The Sensitivity of SeaWiFS Ocean Color Retrievals to Aerosol Amount and Type, J. Atmos. Oceanic Technol., 33, 1185-1209, doi:10.1175/JTECH-D-15-0121.1.

Limbacher, J.A., and R.A. Kahn (2015), MISR empirical stray light corrections in high-contrast scenes, Atmos. Meas. Tech., 8, 1-17, doi:10.5194/amt-8-1-2015.

Limbacher, J.A., and R.A. Kahn (2017), Updated MISR dark water research aerosol retrieval algorithm – Part 1: Coupled 1.1 km ocean surface chlorophyll a retrievals with empirical calibration corrections, Atmos. Meas. Tech., 10, 1539-1555, doi:10.5194/amt-10-1539-2017.

Limbacher, J.A., and R.A. Kahn (2019), Updated MISR over-water research aerosol retrieval algorithm – Part 2: A multi-angle aerosol retrieval algorithm for shallow, turbid, oligotrophic, and eutrophic waters, Atmos. Meas. Tech., 12, 675-689, doi:10.5194/amt-12-675-2019.