Wednesday, 9 January 2013
Exhibit Hall 3 (Austin Convention Center)
Data produced from tracking the movement and life cycle of storms on the globe are particularly useful for validating predictions from global models and for nowcasting of severe storms. These Lagrangian descriptions of the storms are made possible by the merged GEO environmental satellites data. Infrared measurements from new and future environmental satellite systems allow for a comprehensive global picture of storm tracks, classifications, characteristics, and lifecycles. Such an understanding will help assess current satellite capabilities and provide a validation for future missions. Also, user research communities require this information to (1) improve meteorological forecasts with storm tracks and lifecycles information, (2) quantify individual storm contributions to the water cycle, and (3) enhance predictive capacity for regions impacted by natural hazards. Additionally, the resulting characterization leads to a storm classification scheme that can be universally applied rather than study-specific. Distinguishing storm systems can improve GOES-R ABI cloud and precipitation data products.
To characterize and classify our planet's storm systems, this study utilized ForTraCC (Vila et al., 2008), a cloud area-overlap tracking technique, and the NCEP/CPC globally merged, half hourly infrared brightness temperature data product. The dataset (merged from GOES, METOSAT, and GMS) makes this analysis possible due to its fine spatial and temporal resolutions, which are needed to capture a wide range of storm events and features. From preliminary data, the average lifetimes and regions of storm formation were captured using ForTraCC. Characteristics of storms with specific lifetimes were calculated, such as cloud top temperatures and storm cluster sizes. Also, the number of events with a given lifetime was quantified. This submission will highlight the results obtained from longer periods of time; from this analysis, storm systems can be classified into types based on meteorological definitions.
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