Aerosol-cloud interactions are both uncertain and important in global
and regional climate models, and especially in the southeast Atlantic
Ocean. This uncertainty in the region is largely due to two correlated
factors---the expansive, bright, semi-permanent stratocumulus cloud deck
and the fact that southern Africa is the largest source of
biomass-burning aerosols in the world. We study this region using the
WRF-Chem model with CAM5 aerosols and in situ observations from the
ORACLES and LASIC field campaigns in August-October of 2016 through
2018. We compare aerosol and cloud properties to measure and improve
model performance and expand upon observational findings of
aerosol-cloud effects. Relevant comparison variables include aerosol
number concentration, mean particle diameter and spread, CCN activation
tendency, hygroscopicity, and cloud droplet number concentrations.
Specifically, our approach is to analyze colocated model data along
flight tracks to resolve aerosol-cloud interactions. Within and between
single-day flights, there is high spatiotemporal variability that can
get lost to large-scale averaging analyses. We have found that CCN is
substantially under-represented in the model compared to observations.
For a given aerosol number concentration, size, supersaturation and
hygroscopicity, the model will consider fewer particles as CCN than
observations indicate. We plan to explore this result further,
diagnosing the model-observation differences more consistently and
updating the model with more physically accurate values of aerosol size,
concentration, or hygroscopicity based on observations. We will also
intercompare multiple instrument platforms involved with the ORACLES and
LASIC campaigns. With improved small-scale aerosol-cloud interactions,
this work also shows promise to substantially improve that
representation in climate models.