Characterizing the Mesoscale Cellular Convection in Marine Cold Air
Outbreaks with a Machine Learning Approach
Abstract
During marine cold-air outbreaks (MCAOs), when cold polar air moves over
warmer ocean, a well-recognized cloud pattern develops, with open or
closed mesoscale cellular convection (MCC) at larger fetch over open
water. The Cold-Air Outbreaks in the Marine Boundary Layer Experiment
(COMBLE) provided a comprehensive set of ground-based in-situ and remote
sensing observations of MCAOs at a coastal location in northern Norway.
We determine MCAO periods that unambiguously exhibit open or closed MCC.
Individual cells observed with a profiling Ka-band radar are identified
using a water segmentation method. Using self-organizing maps (SOMs),
these cells are then objectively classified based on the variability in
their vertical structure. The SOM-based classification shows that
comparatively intense convection occurs only in open MCC. This
convection undergoes an apparent lifecycle. Developing cells are
associated with stronger updrafts, large spectral width, larger amounts
of liquid water, lower precipitation rates, and lower cloud tops than
mature and weakening cells. The weakening of these cells is associated
with the development of precipitation-induced cold pools. The SOM
classification also reveals less intense convection, with a similar
lifecycle. Such convection, when weakening, becomes virtually
indistinguishable from the more intense stratiform precipitation cores
in closed MCC. Non-precipitating stratiform cores have weak vertical
drafts and are almost exclusively found during closed MCC periods.
Convection is observed only occasionally in the closed MCC environment.