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Evaluation of geostationary satellite observations and the development of a 1–2 h prediction model for future storm intensity
Author(s) -
Mecikalski John R.,
Rosenfeld Daniel,
Manzato Agostino
Publication year - 2016
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2016jd024768
Subject(s) - geostationary orbit , storm , meteorology , climatology , environmental science , satellite , geostationary operational environmental satellite , convective storm detection , pixel , severe weather , intensity (physics) , cloud top , tropical cyclone , geography , geology , computer science , physics , artificial intelligence , quantum mechanics , astronomy
A study was conducted to gain insights into the use of geostationary satellite‐based indicators for characterizing and identifying growing cumulus clouds that evolve into severe weather producing convective storms. Eleven convective initiation (CI), 41 cloud top temperature–effective radius ( T‐r e ), and 9 additional fields were formed for 340 growing cumulus clouds that were manually tracked for 2 h and checked for association with severe weather to 2–3 h into the future. The geostationary satellite data were at 5 min resolution from Meteosat‐8 on six convectively active days in 2010, 2012, and 2013. The study's goals were to determine which satellite fields are useful to forecasting severe storms and to form a simple model for predicting future storm intensity. The CI fields were applied on 3 × 3 pixel regions, and the T‐r e fields were analyzed on 9 × 9 and 51 × 51 pixel domains (needed when forming T‐r e vertical profiles). Of the 340 growing cumulus clouds examined, 34 were later associated with severe weather (using European Severe Weather Database reports), with the remaining being nonsevere storms. Using a multivariate analysis, transforming predictors into their empirical posterior probability, and maximizing the Peirce skill score, the best predictors were T 1451 (51 × 51 pixel T , where r e exceeds 14 µm), T G 9 (9 × 9 pixel glaciation T surrounding a growing cloud), and Re BRTG51 (51 × 51 pixel r e at the breakpoint T in the T‐r e profile). Rapid cloud growth prior to severe storm formation leads to delayed particle growth, colder temperatures of the first 14 µm particles, and lower T G values.