Linking the behaviour of deep convective cores to anvil cloud lifecycles in GOES-16 observations

Abstract:

Improving our understanding of the behaviour of deep convective clouds (DCCs) is vital both for the accurate forecasting of extreme weather events such as lightning, hail and heavy precipitation, and for predicting how the distribution of precipitation and extreme weather events will evolve in a changing climate. Although it is known that heavy precipitation from DCCs is becoming a larger proportion of total precipitation with warming temperatures, there is disagreement in predictions over whether this is due to an increase in the intensity of individual DCCs, or due to an increase in their frequency. Furthermore, there remains great uncertainty in the interactions and feedbacks between the development of DCCs. By tracking and analysing the behaviour of deep convective cores and their associated anvil clouds in geostationary satellite imagery, we can provide new observational constraints of the interactions and feedbacks influencing DCC lifecycles.

We introduce a novel detection and tracking methodology for DCCs that is capable of detecting both growing convective cores and the associated anvil clouds, even after the cores are no longer active. Using optical flow techniques, we construct a perspective to track the motion of DCCs in time series of images from the advanced baseline imager (ABI) aboard the geostationary operational environment satellite (GOES) 16. The semi-Lagrangian framework allows the accurate detection of growing convective cores over multiple consecutive images, and the subsequent tracking of the associated anvil cloud over its entire lifetime. Applying this methodology to multiple years of GOES-16 observations over North America produces a large dataset of tracked DCC cores and anvils.

Using this dataset, we investigate how the properties of convective cores impacts the development, extent, lifetime and microphysical and radiative properties of the associated anvil clouds. As a result, the effects of meteorology and convective organisation can be linked to anvil cloud interactions and feedbacks. Observations from the geostationary lightning mapper aboard GOES-16 and ground-based cloud radars are used in addition to ABI observations to attribute extreme weather events to observed DCCs, and investigate how these events relate to changes in core and anvil cloud behaviour.