Electronically steered phased array radar was developed in mid-1960s mainly for military applications. It has the capability of instantaneously and dynamically controlling beam position on a pulse-to-pulse basis, which allows a single radar to perform multiple functions such as search, target tracking, and weapon controls. The recent-installed phased array radar (PAR) at the National Weather Radar Testbed (NWRT) in Norman, Oklahoma is the first phased array system in the nation dedicated to weather radar research and can electronically steer the beam in both azimuth and elevation. Thus, the PAR has the potential for adaptive sensing to dynamically and interactively adapt its operating parameters according to what it perceives the environment of interest. To fully unleash the power of the PAR for adaptive weather sensing, scheduling multiple tasks such as surveillance and tracking of multiple storm cells is a vital component. In other words, all the tasks are competing for radar time and how to schedule them in a sequence to meet the requirement of the update rate for each task is the core of this study. The concept of Time Balance (TB) is introduced to design and dynamically schedule scanning strategies for a number of tasks with the goal of providing rapid update of hazardous regions without compromising data quality. TB is an adaptive process that schedules those competing tasks, by balancing the amount of radar time and the time required by each task. In this work, simulated radar data are used to compare the performance of TB-based scanning strategies with the conventional Volume Coverage Pattern (VCP) used in the operational Weather Surveillance Radar- 1988 Doppler (WSR-88D). Preliminary results have shown that the update time of storm cell with high data quality can be improved significantly using TB. In addition, TB can dynamically and automatically adjust the scanning strategy when a new storm cell enters the radar domain and is detected.