Global Tracking and Life Cycle Analysis of Distinct Storm Species using a Decade of Satellite Observations

Following the Lagrangian trajectories of storms offers scientists a “big picture” of rainfall activity, which can improve measurement and estimation techniques. Tracking individual events is methodologically advantageous because precipitation is influenced by storm frequency, duration, and characteristics. Many of the past studies focused on tracking and characterization of regional deep-convection; our study seeks to extend past work to global phenomena using a decade of satellite data. We will examine a variety of meteorological events from deep convection to frontal systems, which are driven by dissimilar dynamics, size scales, and rainfall regimes. Ultimately, these results can relate the uncertainties in rainfall estimates to a storm's life stage or assist in hazard prediction.

Our group utilized ForTraCC (Vila et al., 2008), a cloud area-overlap tracking algorithm. This technique was applied to 10 years of the half hourly NCEP/CPC 4km IR dataset (Janowiak et al., 2001). While passive microwave directly estimates rainfall, infrared measurements have the fine spatial and temporal resolutions required to capture a wide range of storms. Using the resulting database of storm tracks, we will discuss the global trajectories and concentration of storms and develop a model of storm lifetimes and properties of different meteorological processes. Early results show distinctive characteristics of storms of varying lifetimes and also across different classes of storms. In the spirit of the American Meteorological Society extreme-weather theme for 2014, we will examine the evolution of extreme events, such as the destructive derecho storm of June 2012. These results can be used to validate retrieval algorithms, evaluate weather models, and used to examine extreme events.