Here, the previous work is put in the context by establishing a complete scheduling framework that can be easily implemented for real-time operation on the NWRT PAR. The framework is modular and consists of four processes: (1) a storm identification algorithm, (2) a storm tracking algorithm, (3) a tasks configuration module, and (4) the TB scheduling algorithm. The storm identification algorithm automatically identifies 3D storm cells during the surveillance task so that updated information about the number, locations, and size of storm cells is provided to the tracking and TB algorithms. In this work, the same framework is used to simulate and evaluate the performance of the TB scheduling algorithm on multiple archived weather data cases. The performance of the TB scheduling algorithm can then be characterized by statistical analyses of the error between the theoretical and estimated quality measures. This is the 1st step towards a real-time implementation of the TB scheduling algorithm on the NWRT PAR, which will enable the demonstration of improvements that can be realized with focused, adaptive weather observations.