Precipitating weather systems have life cycles involving formation, evolution, and decay. These systems can translate across spatial regions spanning 1000's of km. Atmospheric scientists, hydrologists, and operational hydrometeorologists are especially interested in understanding how the characteristics of precipitation systems change over time. For example, a topic of current interest is whether global climate change can be observed in the changing characteristics of precipitating weather systems.

Since precipitation occurs in association with systems that evolve and move in time, explicit analysis of these characteristics requires an entity- or object-oriented approach. Such an approach involves identification of the precipitating weather system of interest and measurement of appropriate characteristics of each system. This type of analysis has typically been performed for specific weather phenomena via visual inspection of weather data. Such visual analysis is very labor intensive, therefore studies have been limited to a relatively small datasets. Recently developed automated object-oriented analysis techniques allow for the analysis of massive databases. However, these algorithms provide "snapshots" at individual times, algorithms that allow automated analysis of the temporal evolution of precipitating weather systems have yet to be developed.

Methods of multi-object target tracking are currently being tested using hourly precipitation analyses from NCEP (Stage IV) and high-resolution WRF model forecasts. A report of this ongoing work will be presented at the conference.