scholarly journals A Climatology of Thunderstorms across Europe from a Synthesis of Multiple Data Sources

2019 ◽  
Vol 32 (6) ◽  
pp. 1813-1837 ◽  
Author(s):  
Mateusz Taszarek ◽  
John Allen ◽  
Tomáš Púčik ◽  
Pieter Groenemeijer ◽  
Bartosz Czernecki ◽  
...  
Keyword(s):  
Central Europe ◽  
Detection System ◽  
Thunderstorm Activity ◽  
Severe Weather ◽  
Data Sources ◽  
Annual Number ◽  
Central Mediterranean ◽  
Severe Thunderstorm ◽  
Lightning Detection ◽  
The Alps

Abstract The climatology of (severe) thunderstorm days is investigated on a pan-European scale for the period of 1979–2017. For this purpose, sounding measurements, surface observations, lightning data from ZEUS (a European-wide lightning detection system) and European Cooperation for Lightning Detection (EUCLID), ERA-Interim, and severe weather reports are compared and their respective strengths and weaknesses are discussed. The research focuses on the annual cycles in thunderstorm activity and their spatial variability. According to all datasets thunderstorms are the most frequent in the central Mediterranean, the Alps, the Balkan Peninsula, and the Carpathians. Proxies for severe thunderstorm environments show similar patterns, but severe weather reports instead have their highest frequency over central Europe. Annual peak thunderstorm activity is in July and August over northern, eastern, and central Europe, contrasting with peaks in May and June over western and southeastern Europe. The Mediterranean, driven by the warm waters, has predominant activity in the fall (western part) and winter (eastern part) while the nearby Iberian Peninsula and eastern Turkey have peaks in April and May. Trend analysis of the mean annual number of days with thunderstorms since 1979 indicates an increase over the Alps and central, southeastern, and eastern Europe with a decrease over the southwest. Multiannual changes refer also to changes in the pattern of the annual cycle. Comparison of different data sources revealed that although lightning data provide the most objective sampling of thunderstorm activity, short operating periods and areas devoid of sensors limit their utility. In contrast, reanalysis complements these disadvantages to provide a longer climatology, but is prone to errors related to modeling thunderstorm occurrence and the numerical simulation itself.

scholarly journals Detecting Severe Weather Trends Using an Additive Regressive Convective Hazard Model (AR-CHaMo)

2018 ◽  
Vol 57 (3) ◽  
pp. 569-587 ◽  
Author(s):  
Anja T. Rädler ◽  
Pieter Groenemeijer ◽  
Eberhard Faust ◽  
Robert Sausen
Keyword(s):  
Spatial Distribution ◽  
Central Europe ◽  
Wind Shear ◽  
Reanalysis Data ◽  
Severe Weather ◽  
Model Data ◽  
Modeling Framework ◽  
Annual Cycles ◽  
Wind Hazard ◽  
The Alps

AbstractA statistical model for the occurrence of convective hazards was developed and applied to reanalysis data to detect multidecadal trends in hazard frequency. The modeling framework is based on an additive logistic regression for observed hazards that exploits predictors derived from numerical model data. The regression predicts the probability of a severe hazard, which is considered as a product of two components: the probability that a storm occurs and the probability of the severe hazard, given the presence of a storm [P(severe) = P(storm) × P(severe|storm)]. The model was developed using lightning data as an indication of thunderstorm occurrence and hazard reports across central Europe. Although it uses only two predictors per component, it is capable of reproducing the observed spatial distribution of lightning and yields realistic annual cycles of lightning, hail, and wind fairly accurately. The model was applied to ERA-Interim (1979–2016) across Europe to detect any changes in lightning, hail, and wind hazard occurrence. The frequency of conditions favoring lightning, wind, and large hail has increased across large parts of Europe, with the exception of the southwest. The resulting predicted occurrence of 6-hourly periods with lightning, wind, and large hail has increased by 16%, 29%, and 41%, respectively, across western and central Europe and by 23%, 56%, and 86% across Germany and the Alps during the period considered. It is shown that these changes are caused by increased instability in the reanalysis rather than by changes in midtropospheric moisture or wind shear.

scholarly journals A Total Lightning Trending Algorithm to Identify Severe Thunderstorms

2010 ◽  
Vol 27 (1) ◽  
pp. 3-22 ◽  
Author(s):  
Patrick N. Gatlin ◽  
Steven J. Goodman
Keyword(s):  
Severe Weather ◽  
Lightning Flash ◽  
Severe Thunderstorm ◽  
Critical Success ◽  
Severe Thunderstorms ◽  
Weather Events ◽  
Total Lightning ◽  
Jump Algorithm ◽  
Early Indication ◽  
Critical Success Index

Abstract An algorithm that provides an early indication of impending severe weather from observed trends in thunderstorm total lightning flash rates has been developed. The algorithm framework has been tested on 20 thunderstorms, including 1 nonsevere storm, which occurred over the course of six separate days during the spring months of 2002 and 2003. The identified surges in lightning rate (or jumps) are compared against 110 documented severe weather events produced by these thunderstorms as they moved across portions of northern Alabama and southern Tennessee. Lightning jumps precede 90% of these severe weather events, with as much as a 27-min advance notification of impending severe weather on the ground. However, 37% of lightning jumps are not followed by severe weather reports. Various configurations of the algorithm are tested, and the highest critical success index attained is 0.49. Results suggest that this lightning jump algorithm may be a useful operational diagnostic tool for severe thunderstorm potential.

System of Warning about Dangerous Atmospheric Phenomena in the North Caucasus for Objects of Economic Activity

2018 ◽  
Vol 931 ◽  
pp. 1019-1024
Author(s):  
Vitaliy A. Shapovalov
Keyword(s):  
Land Reclamation ◽  
Detection System ◽  
Radar Data ◽  
Automated System ◽  
Insurance Companies ◽  
North Caucasus ◽  
Weather Radars ◽  
The North ◽  
Lightning Detection ◽  
Atmospheric Phenomena

This paper presents the developed program-mathematical software for receiving, archiving, analysis and display of radar, lightning and satellite data on clouds and precipitation, interfacing of meteorological information. The program of processing of meteorological information "GIMET-2010" is established on a network of weather radars DMRL-C of the Russian Federation. An automated system combining radar and lightning detection system information applies to the command posts of the uniformed services on the fight against hail and centers of severe storm warning. Following items are provided: a receiving and transmitting to consumers the operational radar data on the actual weather; the detection, identification, and warning of hazardous weather phenomena for airports and populated areas; measurement of the intensity and amount of precipitation for agriculture, hydrological forecasts and land reclamation; obtaining precipitation map for agriculture and insurance companies.

scholarly journals Benchmark campaign and case study episode in Central Europe for development and assessment of advanced GNSS tropospheric models and products

2016 ◽  
Author(s):  
J. Douša ◽  
G. Dick ◽  
M. Kačmařík ◽  
R. Brožková ◽  
F. Zus ◽  
...  
Keyword(s):  
Central Europe ◽  
Functional Model ◽  
Heavy Precipitation ◽  
Severe Weather ◽  
Path Delay ◽  
Numerical Weather ◽  
Horizontal Gradients ◽  
Numerical Weather Models ◽  
Zenith Path Delay ◽  
Weather Models

Abstract. Initial objectives and design of the Benchmark campaign organized within the European COST Action ES1206 (2013-2017) are described in the paper. This campaign has aimed at supporting the development and validation of advanced GNSS tropospheric products, in particular high-resolution and ultra-fast zenith total delays (ZTD) and tropospheric gradients derived from a dense permanent network. A complex dataset was collected for the 8-week period when several extreme heavy precipitation episodes occurred in central Europe which caused severe river floods in this area. An initial processing of data sets from Global Navigation Satellite System (GNSS) and numerical weather models (NWM) provided independently estimated reference parameters – zenith tropospheric delays and tropospheric horizontal gradients. Their provision gave an overview about the product similarities and complementarities and thus a potential for improving a synergy in their optimal exploitations in future. Reference GNSS and NWM results were inter-compared and visually analysed using animated maps. ZTDs from two reference GNSS solutions compared to global ERA-Interim re-analysis resulted in the accuracy at the 10-millimeter level in terms of RMS (with a negligible overall bias), comparisons to global GFS forecast showed accuracy at the 12-millimeter level with the overall bias of -5 mm and, finally, comparisons to mesoscale ALADIN-CZ forecast resulted in the accuracy at the 8-milllimetre level with a negligible total bias. The comparison of horizontal tropospheric gradients from GNSS and NWM data demonstrated a very good agreement among independent solutions with negligible biases and the accuracy of about 0.5 mm. Visual comparisons of maps of zenith wet delays and tropospheric horizontal gradients showed very promising results for future exploitations of advanced GNSS tropospheric products in meteorological applications such as severe weather event monitoring and weather nowcasting. The GNSS products revealed a capability of providing more detailed structures in atmosphere than the state-of-the-art numerical weather models are able to capture. Initial study on contribution of hydrometeors (e.g. cloud water, ice or snow) to GNSS signal delays during severe weather reached up to 17 mm in zenith path delay and suggested to carefully account them within the functional model. The reference products will be further exploited in various specific studies using the Benchmark dataset. It is thus going to play a key role in these highly inter-disciplinary developments towards better mutual benefits from advanced GNSS and meteorological products.

scholarly journals An analysis of manual and autoanalysis for submicrosecond parameters in the typical first lightning return stroke

2021 ◽  
Vol 23 (3) ◽  
pp. 1451
Author(s):  
Muhammad Akmal Bahari ◽  
Zikri Abadi Baharudin ◽  
Tole Sutikno ◽  
Ahmad Idil Abdul Rahman ◽  
Mohd Ariff Mat Hanafiah ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Detection System ◽  
Programming Technique ◽  
Return Stroke ◽  
Zero Crossing ◽  
Manual Analysis ◽  
Lightning Detection ◽  
Crossing Time ◽  
Rising Time ◽  
Initial Peak

The mechanism on how lightning detection system (LDS) operated never been exposed by manufacturer since it was confidential. This scenario motivated the authors to explore the issue above by using MATLAB to develop autoanalysis software based on the feature extraction. This extraction is intended for recognizing the parameters in the first return stroke, and compare the measurement between the autoanalysis software and the manual analysis. This paper is a modification based on a previous work regarding autoanalysis of zero-crossing time and initial peak of return stroke using features extraction programming technique. Further, the parameter on rising time of initial peak is added in this autoanalysis programming technique. Finally, the manual analysis using WaveStudio (LeCroy product) of those two lightning parameters is compared with autoanalysis software. This study found that the autoanalysis produce similar result with the manual analysis, hence proved the reliability of this software.

Nomenclatural and taxonomic notes on Rubus sect. Corylifolii (Rosaceae) in Central Europe

Phytotaxa ◽  
2019 ◽  
Vol 388 (1) ◽  
pp. 107 ◽  
Author(s):  
GERGELY KIRÁLY
Keyword(s):  
Central Europe ◽  
Field Studies ◽  
Morphological Characterization ◽  
Type Material ◽  
Original Material ◽  
Long Time ◽  
The Alps ◽  
Locus Classicus

During recent herbarium and field studies three names of Rubus sect. Corylifolii ser. Subcanescentes were re-assessed. Rubus macrostemonides was typified with a neotype specimen from Salzburg (Austria), and its identity with R. baruthicus was shown (the previous name has the priority). Its presence at the Austrian locus classicus was confirmed also recently, this locality represents the easternmost occurrence of the species. The name R. holosericeus was (mis)applied for a long time for a widespread taxon occurring southeast of the Alps that is not at all present in the original material. This name was lectotypified with a specimen from Styria (Austria) here as a hitherto overlooked regional species recently recorded in Austria, Hungary and Slovenia. The taxon that was formerly (mis)identified as R. holosericeus has proven to be identical to R. semitomentosus, which is lectotypified here with a specimen from Hungary. For both taxa clarified here is, beside a circumstantial assessment of the type material, an improved morphological characterization and circumscription of distribution and habitats presented.

scholarly journals A 5 km Resolution Regional Climate Simulation for Central Europe: Performance in High Mountain Areas and Seasonal, Regional and Elevation-Dependent Variations

Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 682 ◽  
Author(s):  
Michael Warscher ◽  
Sven Wagner ◽  
Thomas Marke ◽  
Patrick Laux ◽  
Gerhard Smiatek ◽  
...  
Keyword(s):  
Wind Speed ◽  
Central Europe ◽  
Large Scale ◽  
Regional Climate ◽  
Climate Simulation ◽  
Wave Radiation ◽  
Historical Period ◽  
High Mountain ◽  
Regional Climate Simulation ◽  
The Alps

Mountain regions with complex orography are a particular challenge for regional climate simulations. High spatial resolution is required to account for the high spatial variability in meteorological conditions. This study presents a very high-resolution regional climate simulation (5 km) using the Weather Research and Forecasting Model (WRF) for the central part of Europe including the Alps. Global boundaries are dynamically downscaled for the historical period 1980–2009 (ERA-Interim and MPI-ESM), and for the near future period 2020–2049 (MPI-ESM, scenario RCP4.5). Model results are compared to gridded observation datasets and to data from a dense meteorological station network in the Berchtesgaden Alps (Germany). Averaged for the Alps, the mean bias in temperature is about −0.3 °C, whereas precipitation is overestimated by +14% to +19%. R 2 values for hourly, daily and monthly temperature range between 0.71 and 0.99. Temporal precipitation dynamics are well reproduced at daily and monthly scales (R 2 between 0.36 and 0.85), but are not well captured at hourly scale. The spatial patterns, seasonal distributions, and elevation-dependencies of the climate change signals are investigated. Mean warming in Central Europe exhibits a temperature increase between 0.44 °C and 1.59 °C and is strongest in winter and spring. An elevation-dependent warming is found for different specific regions and seasons, but is absent in others. Annual precipitation changes between −4% and +25% in Central Europe. The change signals for humidity, wind speed, and incoming short-wave radiation are small, but they show distinct spatial and elevation-dependent patterns. On large-scale spatial and temporal averages, the presented 5 km RCM setup has in general similar biases as EURO-CORDEX simulations, but it shows very good model performance at the regional and local scale for daily meteorology, and, apart from wind-speed and precipitation, even for hourly values.

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