Evaluation of geostationary satellite observations and the development of a 1–2 h prediction model for future storm intensity

Abstract

AbstractA 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‐re), 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‐re fields were analyzed on 9 × 9 and 51 × 51 pixel domains (needed when forming T‐re 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 T1451 (51 × 51 pixel T, where re exceeds 14 µm), TG9 (9 × 9 pixel glaciation T surrounding a growing cloud), and ReBRTG51 (51 × 51 pixel re at the breakpoint T in the T‐re profile). Rapid cloud growth prior to severe storm formation leads to delayed particle growth, colder temperatures of the first 14 µm particles, and lower TG values.