Aerosol variability, synoptic-scale processes, and their link to the cloud microphysics over the northeast Pacific during MAGIC

Shipborne aerosol measurements collected from October 2012 to September 2013 along 36 transects between the port of Los Angeles, California (33.7 degrees N, 118.2 degrees), and Honolulu, Hawaii (21.3 degrees N, 157.8 degrees W), during the Marine ARM GPCI (Global Energy and Water Cycle Experiment (GEWEX)-Cloud System Study (GCSS)-Pacific Cross-section Intercomparison) Investigation of Clouds campaign are analyzed to determine the circulation patterns that modulate the synoptic and monthly variability of cloud condensation nuclei (CCN) in the boundary layer. Seasonal changes in CCN are evident, with low magnitudes during autumn/winter, and high CCN during spring/summer accompanied with a characteristic westward decrease. CCN monthly evolution is consistent with satellite-derived cloud droplet number concentration N-d from the Moderate Resolution Imaging Spectroradiometer. One-point correlation (r) analysis between the 1000hPa zonal wind time series over a region between 125 degrees W and 135 degrees W, 35 degrees N and 45 degrees N, and the N-d field yields a negative r (up to -0.55) over a domain that covers a zonal extent of at least 20 degrees from the California shoreline, indicating that N-d decreases when the zonal wind intensifies. The negative r expands southwestward as the zonal wind precedes N-d by up to 3days, suggesting a transport mechanism from the coast of North America mediated by the California low-coastal jet, which intensifies in summer when the aerosol concentration and N-d reach a maximum. A first assessment of aerosol-cloud interaction (ACI) is performed by combining CCN and satellite N-d values from the Fifteenth Geostationary Operational Environmental Satellite. The CCN-N-d correlation is 0.66-0.69, and the ACI metric defined as ACI=ln(N-d)/ln(CCN) is high at 0.9, similar to other aircraft-based studies and substantially greater than those inferred from satellites and climate models.