Development of an Automated Algorithm to Detect and Track Developing and Mesoscale Convective Systems

Abstract

An objective algorithm is developed which is capable of identifying convective cloud clusters (CCCs) at the point of initiation, tracking any selected of all identified CCCs to maturity (MCS) and then to the point of dissipation and thereby accumulating some physical, morphological and radiative properties. The technique is able to account for periods of growth, propagating, merging, splitting and decaying, which take place during the lifetime of an individual cluster. The algorithm was tested using brightness temperature from merged infrared images of at least eight reporting geostationary satellites or channels at a spatial resolution of 4 Km and temporal resolutions of 30 minutes. The model data used is Weather Research and Forecasting (WRF) with the Advanced Research WRF (ARW) core simulated using the same spatial and temporal resolution with the satellite data for uniform comparison. This was the first attempt of developing such algorithm taking into consideration the uniqueness of West African convective systems. The algorithm loads an input (text) file where necessary inputs as preferred by the user, takes input file of satellite data or model’s output in netcdf file format. The good graphical interface for interacting with user makes it very flexible and easy to use with little computer knowledge. Good results from the comparison and validation shows a good agreement between the model’s output and satellite data shows the consistency in the tracking algorithm. The algorithm can hence be used for comparison or evaluating the performances of different Physics parameterizations/schemes in same model with the observed. It can also be used for comparison or evaluating performances of different models in simulating convective systems of the West Africa sub-region. Keywords : convective systems, tracking, properties, propagation, growth and decaying. DOI: 10.7176/JNSR/13-18-06 Publication date: October 31 st 2022