th 5 European Conference on Severe Storms 12 - 16 October 2009 - Landshut - GERMANY ECSS 2009 Abstracts by session ECSS 2009 - 5th European Conference on Severe Storms 12-16 October 2009 - Landshut – GERMANY List of the abstract accepted for presentation at the conference: O – Oral presentation P – Poster presentation Session 05: Forecasting, nowcasting and warning of severe storms Page Type Abstract Title Author(s) P. Groenemeijer, J. Dahl, C. Probabilistic severe weather forecasting at the European 111 O Gatzen, T. Púčik, O. Schlenczek, Storm Forecasting Experiment (ESTOFEX) H. Tuschy, O. van der Velde Sounding-derived indices for forecasting hailstorms using 113 O A. Manzato ensembles of artificial neural networks O Severe local storm forecasting in the British Isles P. Knightley Forecasting QPF uncertainty for heavy rainfalls produced D. Rezacova, P. Zacharov 115 O by local convective storms A diagnostic tool based on MSG 6.2/7.3µm channel for the P. Santurette, C. Georgiev, C. 117 O analysis and forecasting of deep convection Piriou Comparison of several Ensemble Prediction Systems M. Vich, R. Romero, V. Homar O applied to Mediterranean high impact cyclones associated with heavy rainfall and strong winds Convective parameters computed with ALADIN and P. Marquet, P. Santurette 119 O AROME models for the Hautmont (F4) tornado C. Forster, A. Tafferner, T. Nowcasting of thunderstorms within a weather information 121 O Zinner, H. Mannstein, S. Sénési, and management system for flight safety Y. Guillou Objective NearCasts of convective destabilization prior to O isolated summer-time convective events using moisture R. Petersen, R. Aune products from Geostationary satellites O Operational use of satellite and radar products at Portugal P. Leitão Nowcasting thunderstorm activity across the C. Price, M. Kohn, E. Galanti, K. 123 O Mediterranean Lagouvardos, V. Kotroni Temporal Evolution of Total Lightning and Radar V. Meyer, H. Höller, H.-D. Betz, 125 O Parameters of Thunderstorms in Southern Germany and K. Schmidt its Benefit for Nowcasting Analysis of Thunderstorms with the Dynamic State Index T. Schartner, P. Névir, G. C. 127 O (DSI) in a Limited Area High Resolution Model Leckebusch, U. Ulbrich 129 O A waterspout forecasting technique W. Szilagyi 131 O Tornadoes in Germany – Current developments at DWD A. Friedrich Nowcasting and Warning in convective weather situations D. Murer O at MeteoSwiss 109 Page Type Abstract Title Author(s) A. G. Keul, A. M. Holzer, P. 133 O Are Austrian radio weather warnings user-friendly? Sterzinger, S. Rudolf, A. Reinmueller Convective-scale Data Assimilation and Numerical M. Xue O Weather Prediction at the Center for Analysis and Prediction of Storms: A Status Update 'À la carte' ensemble perturbations with customizable scale V. Homar, D. J. Stensrud O and amplitude J. S. Kain, S. J. Weiss, M. C. New developments in applied research for severe Coniglio, M. Xue, F. Kong, M. 135 O convection forecasting in the Hazardous Weather Weisman, M. Pyle, R. Sobash, C. Testbed, Norman, OK, U.S.A. Schwartz, D. Bright, J. Levit, G. Carbin. A cloud model study of wind shear effect on the satellite P. K. Wang 137 O observed storm top IR features Recent advances in precipitation nowcasting at the RMI of M. Reyniers, L. Delobbe, P. 139 O Belgium: storm severity product Dierickx, M. Thunus, C. Tricot Predictability of Extreme Storm Events in the State of São G. Held, A. M. Gomes, M. 141 P Paulo, Brazil Teixeira, J. M. Bassan Detection Parameters of Thunderstorms: adaptation of A. C. Nóbile Tomaziello, A. W. P thresholds to Metropolitan Region of São Paulo, BRA Gandu Nowcasting of severe storm at a station by using the soft S. Sharma, D. Dutta, J. Das, R. 143 P computing techniques to the radar imagery M. Gairola Extreme Events in the Amazônia Region during the Rainy J. Saraiva, J. L. M. Lopes, R. H. P Season of 2009 Braga, G. G. Ribeir A proposed air masses classification for the Mediterranean T. la Rocca P to predict severe weather A. Udogwu, J. B. Omotosho, S. Forecasting and Nowcasting of Severe Storms and their 145 P Gbuyiro, I. Ebenebe, G.C Osague, Preferred Tracks across West Africa E. Olaniyan West African weather system in the development of tropical T. Salami, O. S. Idowu, E. E. P cyclones Balogun Nowcasting and assessing thunderstorm risk on Lombardy P. Bonelli, P. Marcacci, E. 147 P Region (Italy) Bertolotti, E. Collino,G. Stella 149 P Triggering of deep convection by low-level boundaries K. J. Rae J. L. Sánchez, L. López, B. Gil- Short-term forecast of hail precipitation parameters 151 P Robles, J. Dessens, C. Bustos, C. Berthet. Precipitation forecast by the COSMO NWP model using 153 P Z. Sokol, P. Pesice radar and satellite data 155 P Non Mesocyclone Tornadoes in Hungary Z. Polyánszky A statistical study of stability indices as convective weather M. Salvati, D. Berlusconi 157 P predictors in Lombardia P Diagnostic tool convective modes R. Groenland, R. van Westrhenen 110 5h European Conference on Severe Storms 12 - 16 October 2009 - Landshut - GERMANY PROBABILISTIC SEVERE WEATHER FORECASTING AT THE EUROPEAN STORM FORECAST EXPERIMENT P.Groenemeijer1, J. Dahl2, C. Gatzen3, T. Púčik4, O.Schlenczek5, H. Tuschy6, O. van der Velde7 1 Institute of Meteorology, University of Munich, Germany, [email protected] 2 Institute for Atmospheric Physics, German Aerospace Center DLR, Oberpfaffenhofen, Germany 3 Meteogroup Deutschland, Berlin, Germany 4 Faculty of Natural Sciences, Masaryk University, Brno, Czech Republic 5 Institute for Atmospheric Physics, Johannes Gutenberg-University, Mainz, Germany 6 Institute of Meteorology and Geophysics, Leopold-Franzens-University, Innsbruck, Austria 7 Lightning Research Group, Technical University of Catalonia (UPC), Terrassa, Spain 1. INTRODUCTION a person within an threat level area to experience severe The European Storm Forecast Experiment (ESTOFEX) weather”, which is arguably the most elementary quantity to issues Storm Forecasts that provide an assessment of the forecast, cannot be verified using the dataset. severe convective storm risk, that is the threat of large hail, convective wind gusts, tornadoes and recently, excessive precipitation across Europe (Dahl et al., 2004). These risk estimates are communicated in a forecast text, and more precisely in a map that assigns threat levels to specific areas in Europe. Four threat levels are used, three of which are numbered on the forecast maps: 1, 2 and 3. Level 0 is implied where no level 1, 2 or 3 is indicated. The assigned threat level is determined by a meteorologist who weighs several types of information including data from global and regional numerical models, and observational data from satellites, radiosondes, and surface networks. The threat level system as it was used until 1 May 2009 described the number of severe events to be expected within a 200 km x 200 km area for each threat level area, but this proved to be a difficult criterion for forecasters to work with. To users, it was not easy either to derive the probability of experiencing severe weather within a particular threat level. Still forecast verification could be carried out, for some methods do not require the risk level to be specified, enabling Brooks et al. (2008) to present verification results FIG 1: Severe weather events in the period considered, 1 May 2008 of ESTOFEX forecasts without having to use the – 30 April 2009. Triangles pointing upward: large hail, pointing troublesome criteria. downward: tornadoes, circles: wind gusts. The dark contour denotes The wish to develop an straightforward and usable the area across which the analysis has been performed. definitions of the probability of severe weather in each threat level remained a goal of the team. In what follows, the The obvious solution to this conundrum is to specify an method of deriving those will be explained. arbitrary area of vicinity. We have chosen a circle of 40 km, which is comparable with the 25 nautical miles radius used II. METHOD by the U.S. Storm Prediction Center to facilitate future In making the transition from a qualitative to a quantitative comparisons. The predictand of the forecasts was formally forecast scheme, it was decided not to discard the old threat defined as: levels, but rather to quantitatively define the threat levels that were already used. To find the corresponding probability “The probability that one or more severe weather events values, an a posteriori analysis of the average frequency of occur within a circle with radius 40 km of a point” severe weather in the threat areas was performed. Such an exercise would ideally make use of a dataset that contains all severe weather events that occurred, and the size of the area severe weather extremely severe affected by each event. Naturally, such a dataset does not weather exist. The dataset that comes closest to this is the severe hail ≥ 2 cm ≥ 5 cm weather database ESWD (Dotzek et al., 2009), managed by tornado any ≥ F2 the European Severe Storms Laboratory. This dataset however, contains severe weather events as points in space wind gust ≥ 25 m/s ≥ 32 m/s and time. The size of the area affected by the event is TABLE. 1: Fraction of rectangles contained within each threat level normally not available. This implies that “the probability of area that was labelled “severe” and “extremely severe”, respectively. 111 The procedure was repeated with severe weather replaced by extremely severe weather. For definitions of these concepts, please refer to Table 1. Subsequently, a part of the forecast area of Estofex was selected as the domain for the analysis (see Fig. 1). Within this area, which includes the Benelux, Germany, the Alps, Hungary, the Czech Republic, Slovakia and Poland, active storm spotter networks provided a –subjectively judged– good coverage of severe weather throughout the considered period (1 May 2008 – 30 April 2009). This area was divided into rectangular areas with a surface area corresponding to a circle with radius 40 km.