This study introduces the development of the Tracking Algorithm for Mesoscale Convective Systems (TAMS), an algorithm that allows for the identifying, tracking, classifying, and assigning of rainfall to mesoscale convective systems (MCSs). TAMS combines area-overlapping and projected-cloud-edge tracking techniques to maximize the probability of detecting the progression of a convective system through time, accounting for splits and mergers. The combination of projection on area overlapping is equivalent to setting the background flow in which MCSs are moving on. Sensitivity tests show that area-overlapping technique with no projection (thus, no background flow) underestimates the real propagation speed of MCSs over Africa. The MCS life cycles and propagation derived using TAMS are consistent with climatology. The rainfall assignment is also more reliable than with previous methods as it utilizes a combination of regridding through linear interpolation with high temporal and spatial resolution data. This makes possible the identification of extreme rainfall events associated with intense MCSs more effectively. TAMS will be utilized in future work to build an AEW-MCS dataset to study tropical cyclogenesis.
All Science Journal Classification (ASJC) codes
- Atmospheric Science