Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.

We studied the stability of a blockwise phase correlation (PC) method to estimate cloud motion using a total sky imager (TSI). Shorter frame intervals and larger block sizes improve stability, while image resolution and color channels have minor effects. Raindrop contamination can be identified by the rotational motion of the TSI mirror. The correlations of cloud motion vectors (CMVs) from the PC method with wind data vary from 0.38 to 0.59. Optical flow vectors are more stable than PC vectors.

This study uses in situ aircraft measurements to characterize the size and shape distributions of 10 µm to 6 mm diameter particles observed during six penetrations of wildfire-induced pyroconvection. Particles sampled in one penetration of a smoke plume are most likely pyrometeors composed of ash. The other penetrations are through pyrocumulus clouds where particle composition is most likely a combination of hydrometeors (ice particles) and pyrometeors (ash).

The Earth Model Column Collaboratory (EMC²) is an open-source ground-based (and air- or space-borne) lidar and radar simulator and subcolumn generator designed for large-scale models, in particular climate models, applicable also for high-resolution models. EMC² emulates measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. We demonstrate the use of EMC² to compare AWARE measurements with the NASA GISS ModelE3 and LES.