Abstract

Strong tornadoes are common for the European part of Russia but happen rather rare east of the Urals. June 2017 became an exceptional month when two tornado outbreaks occurred in the Ural region of Russia, yielded $3 million damage, and resulted in 1 fatality and 14 injuries. In this study, we performed detailed analysis of these outbreaks with different data. Tornadoes and tornado-related environments were diagnosed with news and eyewitness reports, ground-based meteorological observations, sounding data, global numerical weather prediction (NWP) models data, synoptic charts, satellite images, and data of specially conducted aerial imaging. We also estimated the accuracy of short-term forecasting of outbreaks with the WRF-ARW mesoscale atmospheric model, which was run in convection-permitting mode. We determined the formation of 28 tornadoes during the first outbreak (3 June 2017) and 9 tornadoes during the second outbreak (18 June 2017). We estimated their intensity using three different approaches and confirmed that, based on the International Fujita scale (IF), one of the tornadoes had the IF4 intensity, being the first IF4 tornado in Russia in the 21st century and the first-ever IF4 tornado reported beyond the Ural Mountains. The synoptic-scale analysis revealed the similarity of two outbreaks, which both formed near the polar front in the warm part of deepening southern cyclones. Such synoptic conditions yield mostly weak tornadoes in European Russia; however, our analysis indicates that these conditions are likely favorable for strong tornadoes over the Ural region. Meso-scale analysis indicates that the environments were favorable for tornado formation in both cases, and most severe-weather indicators exceeded their critical values. Our analysis demonstrates that for the Ural region, like for other regions of the world, combined use of the global NWP model outputs indicating high values of severe-weather indices and the WRF model forecast outputs explicitly simulating tornadic storm formation could be used to predict the high probability of strong tornado formation. For both analyzed events, the availability of such tornado warning forecast could help local authorities to take early actions on population protection.

Highlights

  • Tornadoes are one of the most devastating and hard-to-predict atmospheric phenomena observed in mid-latitudes

  • European Russia; our analysis indicates that these conditions are likely favorable for strong tornadoes over the Ural region

  • The one exception is the tornado that passed near Visim and was covered by high-resolution aerial images. We found this the tornado caused total canopy removal and snapped most coniferous trees within the damage track, while deciduous trees were mostly felled down; as a result, we rated it as IF2 [65]

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Summary

Introduction

Tornadoes are one of the most devastating and hard-to-predict atmospheric phenomena observed in mid-latitudes. Numerous tornado case-studies in Russia and other European countries have appeared based on observations and reanalyses data [6,7,8,9], satellite and aerial images [10,11,12,13], and data from weather radars [8,9,14] These studies focused mostly on post-event damage assessment [10,13,15,16], estimates of mesoscale peculiarities of tornado formation and development [9,12,17,18,19], and refinements of regional values of associated severe-weather indicators (so-called ‘ingredients’) [7,9,17,20].

Overview of the Data Sources
Tornado Tracks Identification and Characteristics Estimate
WRF Model Configuration and Forecast Accuracy Assessment
Storm Events Description
Large-Scale Synoptic Features
Convective Storms Evolution
The Main Characteristics of Tornadoes and Associated Severe Weather Events
June 2017 near
Results of Modeling
Junewith
Validation of the Simulation Results with the Meteosat-8 Images
11. HRV cloudcloud
Sensitivity of Simulation Results to Forecast Lead Time
June and 18
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