Synoptic climatology of tropical and subtropical South America and adjoining seas as inferred from Geostationary Operational Environmental Satellite imagery

Prakki Satyamurty; Marcelo B. Rosa

doi:10.1002/joc.6217

Synoptic climatology of tropical and subtropical South America and adjoining seas as inferred from Geostationary Operational Environmental Satellite imagery

International Journal of Climatology ◽

10.1002/joc.6217 ◽

2019 ◽

Vol 40 (1) ◽

pp. 378-399 ◽

Cited By ~ 2

Author(s):

Prakki Satyamurty ◽

Marcelo B. Rosa

Keyword(s):

South America ◽

Satellite Imagery ◽

Synoptic Climatology ◽

Geostationary Operational Environmental Satellite

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A Preliminary Statistical Study of Correlations between Inflow Feeder Clouds, Supercell or Multicell Thunderstorms, and Severe Weather

Weather and Forecasting ◽

10.1175/2009waf2222149.1 ◽

2009 ◽

Vol 24 (4) ◽

pp. 921-934 ◽

Cited By ~ 5

Author(s):

Rebecca J. Mazur ◽

John F. Weaver ◽

Thomas H. Vonder Haar

Keyword(s):

Satellite Imagery ◽

Statistical Study ◽

Detection Algorithm ◽

Severe Weather ◽

Potential Utility ◽

Geostationary Operational Environmental Satellite ◽

The Relationship ◽

Visible Imagery ◽

Cloud Analysis

Abstract This study examines the relationship between severe weather and organized lines of cumulus towers, called feeder clouds, which form in the inflow region of supercell and multicell thunderstorms. Using Geostationary Operational Environmental Satellite (GOES) imagery, correlations between the occurrence of feeder clouds and severe weather reports are explored. Output from the Weather Surveillance Radar-1988 Doppler (WSR-88D) mesocyclone detection algorithm (MDA) is also assessed for a subset of the satellite case days. Statistics from the satellite and radar datasets are assembled to estimate not only the effectiveness of feeder cloud signatures as sole predictors of severe weather, but also the potential utility of combining feeder cloud analysis with the radar’s MDA output. Results from this study suggest that the formation of feeder clouds as seen in visible satellite imagery is often followed by the occurrence of severe weather in a storm. The study finds that feeder cloud signatures by themselves have low skill in predicting severe weather. However, if feeder clouds are observed in a storm, there is a 77% chance that severe weather will occur within 30 min of the observation. For the cases considered, the MDA turns out to be the more effective predictor of severe weather. However, results show that combined predictions (feeder clouds plus mesocyclones) outperform both feeder cloud signatures and the MDA as separate predictors by ∼10%–20%. Thus, the presence of feeder clouds as observed in visible imagery is a useful adjunct to the MDA in diagnosing a storm’s potential for producing severe weather.

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