Investigation of the temporal variability of thunderstorms in central and western Europe and the relation to large‐scale flow and teleconnection patterns

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A statistically significant link is presented between atmospheric blocking located over the eastern North Atlantic and northern Europe and warm‐season thunderstorm activity over western and central Europe. Lightning data from 2001 to 2014 were used to identify thunderstorm days and blocking events were extracted from the ERA‐Interim reanalysis using an objective identification algorithm. The statistical link between the two phenomena is established through odds ratio analysis. Two areas – one over the eastern part of the North Atlantic and one over the Baltic Sea – were identified as locations where blocking influences the occurrence of deep moist convection in parts of western and central Europe. Based on the mean ambient conditions on days with blocking in these two areas, well‐known dynamic and thermodynamic mechanisms supporting or suppressing the development of thunderstorms were confirmed. The anticyclonic circulation of a block over the eastern part of the North Atlantic leads to a northerly to northwesterly advection of dry and stable air masses into Europe on the eastern flank of the block. In addition, these environmental conditions are on average associated with large‐scale subsidence of air masses (convection‐inhibiting conditions). In contrast, the southerly to southwesterly advection of warm, moist and unstable air masses on the western flank of a block over the Baltic Sea results in convection‐favouring conditions over western and central Europe. Both blocking situations are on average associated with weak wind speeds at mid‐tropospheric levels and with weak wind shear. As a consequence, thunderstorms related to atmospheric blocking over the Baltic Sea tend to be on average less organised.

“…Piper et al . (, their fig. 2) also observed convective cases where regions located below a ridge are frequently characterised by a lack of large‐scale lifting.…”

Section: Environmental Conditions During Blockingmentioning

confidence: 97%

“…; Piper et al . ), which typically peak during late afternoon (Wapler, ; Poelman et al . ; Piper and Kunz, ).…”

Section: Environmental Conditions During Blockingmentioning

confidence: 98%

Section: Environmental Conditions During Blockingmentioning

confidence: 99%

Section: Environmental Conditions During Blockingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Relationship between atmospheric blocking and warm‐season thunderstorms over western and central Europe

Mohr

Wandel

Lenggenhager

et al. 2019

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Hailstorms in the Alpine region: Diurnal cycle, 4D‐characteristics, and the nowcasting potential of lightning properties

Nisi

Hering

Germann

et al. 2020

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Nowcasting of hailstorms still poses a major challenge to weather services, because of the limited availability of reliable large datasets and the short spatio-temporal scales involved. Two novel Eulerian and Lagrangian hail climatologies for the Alps are applied to address important aspects of hailstorms in the Alps: the diurnal cycle, their spatio-temporal development and the lightning properties. The database contains more than 100,000 ordinary and 30,000 hail storms (2002-2017). Based on that large sample of storms, the diurnal cycle of storm initiation and evolution is studied in the context of orographic forcing and cold-front occurrence statistics. Results show that, during daytime, storms mainly initiate over the foothills (Prealps) and move towards areas with higher terrain elevations. During night-time, the storms preferably move from the foothills to the plains. Five out of 16 years of the radar-derived convective storms show a significant yearly positive hail anomaly, from which two years show relative hail-initiation maxima evenly distributed over the 24 hour without a characteristic diurnal cycle. Relative hail maxima during night-time cannot always be explained with a higher occurrence of cold fronts. Time series of storm vertically integrated liquid water content are used to separate ordinary and hail storm development. Differences are found between vertically integrated liquid and its density in cold air-mass storms. Finally, lightning data from a ground-based network are combined with the radar-derived hailstreaks and evaluated with respect to their prediction skill as a function of lead time (flash rate, density, peak current, lightning jumps). Results show that lightning data provide only modest skill-scores in nowcasting hailstorms. Only the sudden increase in lightning rate (referred to as lightning jump) may be used as additional data for hailstorm nowcasting. However, their application in automatic nowcasting systems

Exploring relationships between weather patterns and observed lightning activity for Britain and Ireland

Wilkinson

Neal

2021

To understand the climatology of lightning affecting Britain and Ireland and to investigate the large‐scale environments which produce lightning in this region, relationships between mean sea‐level pressure (MSLP) patterns and thunderstorm occurrence are investigated. Using daily data between 2010 and 2019, instances of lightning activity are examined against a set of 30 pre‐defined weather patterns based on MSLP. Metrics relating to thunder area, thunder intensity and duration are introduced and evaluated on the data set. The results show that in summer the largest and long‐lived lightning outbreaks can be linked to three weather patterns. Two of these have strong southerly flow affecting the domain of study. The third is a low‐pressure system centred over the UK with weak pressure gradient, which also produces larger lightning outbreaks during the autumn. In the wintertime, lightning outbreaks appear associated with deeper low‐pressure systems, higher pressure gradients and strong winds in four dominant weather patterns. In spring, lightning occurs mostly in smaller systems and can be of multiple weather patterns. It is hypothesised that the weather pattern number is a good predictor of atmospheric instability. Cases where lightning activity does not match the expected behaviour for a given weather pattern are thought to be due to anomalies or variation in atmospheric instability. Several applications of this work are also discussed, including looking at thunder days over the study domain in past and future climate scenarios.