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contributor authorCintineo, John L.
contributor authorPavolonis, Michael J.
contributor authorSieglaff, Justin M.
contributor authorHeidinger, Andrew K.
date accessioned2017-06-09T16:49:33Z
date available2017-06-09T16:49:33Z
date copyright2013/09/01
date issued2013
identifier issn1558-8424
identifier otherams-74813.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4217080
description abstracteostationary satellites [e.g., the Geostationary Operational Environmental Satellite (GOES)] provide high temporal resolution of cloud development and motion, which is essential to the study of many mesoscale phenomena, including thunderstorms. Initial research on thunderstorm growth with geostationary imagery focused on the mature stages of storm evolution, whereas more recent research on satellite-observed storm growth has concentrated on convective initiation, often defined arbitrarily as the presence of a given radar echo threshold. This paper seeks to link the temporal trends in robust GOES-derived cloud properties with the future occurrence of severe-weather radar signatures during the development phase of thunderstorm evolution, which includes convective initiation. Two classes of storms (severe and nonsevere) are identified and tracked over time in satellite imagery, providing distributions of satellite growth rates for each class. The relationship between the temporal trends in satellite-derived cloud properties and Next Generation Weather Radar (NEXRAD)-derived storm attributes is used to show that this satellite-based approach can potentially be used to extend severe-weather-warning lead times (with respect to radar-derived signatures), without a substantial increase in false alarms. In addition, the effect of varying temporal sampling is investigated on several storms during a period of GOES super-rapid-scan operations (SRSOR). It is found that, from a satellite perspective, storms evolve significantly on time scales shorter than the current GOES operational scan strategies.
publisherAmerican Meteorological Society
titleEvolution of Severe and Nonsevere Convection Inferred from GOES-Derived Cloud Properties
typeJournal Paper
journal volume52
journal issue9
journal titleJournal of Applied Meteorology and Climatology
identifier doi10.1175/JAMC-D-12-0330.1
journal fristpage2009
journal lastpage2023
treeJournal of Applied Meteorology and Climatology:;2013:;volume( 052 ):;issue: 009
contenttypeFulltext


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