Agostino Manzato

A climatology of instability indices derived from Friuli Venezia Giulia soundings, using three different methods

Abstract In the previous work, “Evaluating the sounding instability with the Lifted Parcel Theory” (hereafter ESI also published in this issue), we described a program which implements the Lifted Parcel Theory in three different ways. In this work, we build a climatology of the sounding-derived instability indices based on 5050 different soundings, made in Udine (WMO code 16044) from April to September 1995–2001. Every 6 h, we associate a sounding with the presence of cloud-to-ground lightning strikes and also with a continuous variable, CALCA6h, built using lightning strikes number, rain and wind gust, measured in the plain of our region. For each of the about 30 indices, we studied the skill score for forecasting the presence of thunderstorms and the linear cross-correlation for forecasting the thunderstorm “intensity”. We also introduce the use of some relatively new indices: the maximum buoyancy, the cloud precipitable water, the mean horizontal vapour flux and the standard deviation of the sounding vertical velocity. Finally, we discuss which indices and which of the three methods are the best in our region for forecasting convective events.

Evaluating the sounding instability with the Lifted Parcel Theory

Abstract The Lifted Parcel Theory is a simple method for evaluating the instability of a sounding and computing a number of instability indices, for forecasting convective events. Very different results are obtained, depending on the choice of the initial parcel to lift and on the method used for evaluating the buoyancy (e.g., using the virtual or cloud-virtual temperature). A new method, which retains the condensed water inside the rising parcel and freezes it progressively and continuously, is investigated. For each of the three methods implemented, the coherent adiabatic processes are applied, and finally, the different results are compared.

The June 4th 1999 severe weather episode in San Quirino, Italy: a tornado event?

Abstract On the morning of June 4th 1999, a severe weather event took place in San Quirino, a small village of Friuli-Venezia Giulia in the northeast of Italy. This village is located near the piedmont of the Alps, 40 km west from Udine and 60 km north from Venice. Around 0900 UTC (1100 local time), a thunderstorm with an intense hail fall affected the area of San Quirino. A few minutes later (around 0920 UTC, source: a farmer), a funnel cloud from a cumulonimbus touched the ground, producing damages to houses, trees and sheds. The damaged area was quite narrow (about 300 m) and short (less than 10 km). No injuries to people were reported. In spite of the smallness of the area interested by the phenomenon, this storm is studied here starting from the synoptic scale, moving to the mesoscale and finishing with the storm scale, trying to underline its characteristics. These analyses, especially those coming from the Doppler radar images, bring us to the conclusion that the San Quirino episode was produced by a supercell storm.

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

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-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 5min 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 14μm), 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 14μmparticles, and lower TG values.