A Review of Satellite Cloud Condensation Nuclei Retrieval Methods for
Evaluation with In-situ Measurements from Aircraft-Based Observations in
the Marine Boundary Layer
Abstract
Aerosol-cloud interactions are the most uncertain component of the Earth
system, due to their major influence on cloud properties, and as a
result, Earth’s energy budget. We need to better characterize these
interactions, which requires constraining the cloud condensation nuclei
(CCN) budget and disentangling the influences of aerosol microphysics
from meteorology. Observational data are essential for evaluating and
improving climate models, but airborne field campaigns have, until
recently, been limited to a few (mostly continental) regions worldwide.
CCN measurements over the remote ocean are scarce and only occur during
extensive field missions involving airborne or ship-based measurements
of limited spatial and temporal extent. Polar-orbiting satellite
observations hold great promise for expanding the spatial coverage of
observations to remote regions, however, it is currently not well
understood to what extent these active and passive remote sensing
observations can be considered adequate proxies for CCN. Recent
literature make use of column integrated retrievals, such as aerosol
optical depth or aerosol index, to characterize aerosol concentration
and CCN, and the utility of vertically resolved optical properties from
active sensors is only now becoming more fully understood. The NASA
ACTIVATE, NAAMES, CAMP2EX and ORACLES field campaigns
are particularly well suited for evaluating the skill of advanced
satellite aerosol and cloud microphysical retrievals, given the
comprehensive suite of airborne aerosol, cloud, and trace gas
measurements, combined with airborne High Spectral Resolution Lidar
(HSRL) and polarimetric imaging instruments that will be the basis for
the next generation of space-based remote sensors. Here, we characterize
the properties of aerosol and CCN from these NASA field campaigns and
critically assess methods for deriving CCN and CCN proxies using visible
and infrared satellite remote sensing retrievals.