Mesoscale Convective System Tracking Algorithm Applicable for South East Asia

Abstract:

Mesoscale Convective Systems are symbols of organized severe convection and are one of the most important weather systems affecting South East Asia (SEA) region. Following one of the latest MCS tracking algorithm using Kalman Filter (Huang X, et al., 2018), we developed a new MCS tracking algorithm applicable for SEA using brightness temperature due to the lacking of radar data available in this region. The key modifications include more accurate estimation of propagation speed of potential MCS that is critical to update the location of potential MCS in Kalman Filter. This is especially helpful to track small MCSs that have high traveling speed or MCSs with abrupt changes of moving direction and center location. Next, the new algorithm tackles the split-and-merge uncertainty using a probabilistic approach.

We establish the SEA MCS database using high spatial-temporal NOAA NCEP/CPC IR brightness temperature (Janowiak J. E., R. J. Joyce, and Y. Yarosh, 2001) and document the basic parameters, including duration, size, center location, speed, direction, etc. Our SEA MCS database captures more short but sizable MCSs in oceanic regions than land. We find that the linear relationship between size and duration found in previous studies is not as explicit. Next, the relationship between precipitation and the spatiotemporal pattern of MCS is explored. Our algorithm offers a considerably easy way to identify MCS in SEA, which can also be implemented in other regions. We anticipate our dataset can serve different research purposes such as MCS-related hazards studies (Tropical Cyclones, extreme precipitation, etc.). Also, we aim to implement our new algorithm and SEA MCS database to promote the understanding of interactions between environmental conditions and MCS development in SEA.