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ACTIVATE
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Gonzalez, M., et al. (2022), Relationships between supermicrometer particle concentrations and cloud water sea salt and dust concentrations: analysis of MONARC and ACTIVATE data, Environmental Science: Atmospheres, doi:10.1039/d2ea00049k.
Schlosser, J.S., et al. (2022), Polarimeter + Lidar–Derived Aerosol Particle Number Concentration, Front. Remote Sens., 3, 885332, doi:10.3389/frsen.2022.885332.
Painemal, D., et al. (2020), Reducing uncertainties in satellite estimates of aerosol–cloud interactions over the subtropical ocean by integrating vertically resolved aerosol observations, Atmos. Chem. Phys., 20, 7167-7177, doi:10.5194/acp-20-7167-2020.
Ouyed, A., et al. (2021), Two-Stage Artificial Intelligence Algorithm for Calculating Moisture-Tracking Atmospheric Motion Vectors, J. Appl. Meteor. Climat., 60, 1671-1684, doi:10.1175/JAMC-D-21-0070.1.
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Li, X.-Y., et al. (2022), Large-Eddy Simulations of Marine Boundary Layer Clouds Associated with Cold-Air Outbreaks during the ACTIVATE Campaign. Part I: Case Setup and Sensitivities to Large-Scale Forcings, J. Atmos. Sci., 79, 73-100, doi:10.1175/JAS-D-21-0123.1.
Dadashazar, H., et al. (2021), Aerosol responses to precipitation along North American air trajectories arriving at Bermuda, Atmos. Chem. Phys., 21, 16121-16141, doi:10.5194/acp-21-16121-2021.