A Source Apportionment Approach to Study the Evolution of Convective Cells: An Application to the Nowcasting of Convective Weather Systems

A new algorithm is developed, based on Source Apportionment (SA) technique for tracking and nowcasting of Mesoscale Convective Systems (MCS) using satellite image sequences. The algorithm does not use the conventional threshold method for identifying convective regions, instead it introduces neighbourhood search criteria to select contiguous pixels. This offers better opportunity for data mining, and inherently provides an automatic method for tracking. The nowcasting scheme is based on growth curve model fitting and extrapolation using time varying coefficients. The methodology proposed in the paper is demonstrated for the life cycle of a MCS. The algorithm is also tested on an ensemble set comprising of thermal infrared image sequences acquired from Kalpana-1 satellite. Error statistics and skill score analysis indicate the operational feasibility of the proposed algorithm.