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

Wilkinson, Jonathan; Neal, Robert A.

doi:10.1002/qj.4099

Cited by 18 publications

(49 citation statements)

References 57 publications

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“…Peaks on NW-and West-facing coasts of Scotland and Ireland (Holt et al, 2001;Wilkinson and Neal, 2021). Shown in Outer Hebrides and Shetland in Autumn (Perry and Hollis, 2005) General orographic lift Peaks in Cumbria and Manchester basin (Holt et al, 2001).…”

Section: Winter Orographic Uplift Of Unstable Polar Maritime Airmentioning

confidence: 99%

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A regional lightning climatology of the UK and Ireland and sensitivity to alternative detection networks

Hayward

Whitworth

Pepin

et al. 2022

Intl Journal of Climatology

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A total lightning (cloud‐ground and cloud‐cloud) climatology of the UK and Ireland is presented combining three different ground‐based lightning location systems over a 12‐year period (2008–2019). The study area is divided into seven geographical regions using k‐means clustering to identify areas with distinctive seasonal distributions of lightning flashes per km2/year (referred to as flash density [FD]). Different regions exhibit contrasting summer thunderstorm seasons (e.g., from April to August in the southeast of England and May to July in southern England coastal regions). Summer FD peaks in July in the English Channel and southeast and midland areas of England range from 0.1 to 0.3 FD whilst the southern England coastal region sees FDs in the range 0.03–0.06 FD. Regions more prone to winter thunderstorms are identified as having northwest facing coastlines (<0.02 FD in Northwest Scotland). Diurnal lightning distributions are also shown to have regional dependence with stronger afternoon peaks over‐land (0.05–0.1 FD in the south of England), whilst in the South coastal and English Channel regions early morning or overnight peaks (0.03–0.09 FD) are more pronounced relative to afternoon FDs (0.015–0.03). This study has demonstrated the benefit of using multiple lightning detection networks to mitigate the effects of inhomogeneities within any one data source. It is also shown that significant additional insight comes from taking a regional approach to analysing temporal distributions of lightning.

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Section: Winter Orographic Uplift Of Unstable Polar Maritime Airmentioning

confidence: 99%

“…London, Manchester and Dublin-peaks in Spring (Wilkinson and Neal, 2021), hotspot in Manchester in Autumn and Winter (Perry and Hollis, 2005).…”

Section: Urban Heat Islandsmentioning

confidence: 99%

A regional lightning climatology of the UK and Ireland and sensitivity to alternative detection networks

Hayward

Whitworth

Pepin

et al. 2022

Intl Journal of Climatology

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“…Sample size limitations with some of the climatologies, particularly for rarer weather patterns, will add an additional level of uncertainty to the resulting forecasts. This is something that was considered by Wilkinson and Neal (2021) in their UK-based weather pattern application for lightning occurrence. In their study, they derived a gridded seasonal lightning climatology for each weather pattern and then merged these with weather pattern forecast probabilities to produce a gridded forecast probability of lightning occurrence (as in Equation ( 3)).…”

Section: Discussionmentioning

confidence: 99%

“…These include forecasting significant wave heights (Steele et al, 2017, 2018), extreme regional rainfall (Richardson, Neal, et al, 2020), coastal flooding (Neal et al, 2018) and flow from Iceland into UK air space for the rapid assessment of volcanic ash risk on aviation given an active Icelandic volcanic eruption (Harrison et al, 2022). Several research applications have also been investigated, including for meteorological droughts (Richardson et al, 2018; Richardson, Fowler, et al, 2020), bike journeys in London (Brown et al, 2019), temperature‐related excess mortality (Huang et al, 2020) and lightning risk (Wilkinson & Neal, 2021). The examples over Europe demonstrate the value of weather pattern forecasts as a medium‐range forecasting guidance tool, which this study hopes to utilize over India.…”

Section: Introductionmentioning

confidence: 99%

The application of predefined weather patterns over India within probabilistic medium‐range forecasting tools for high‐impact weather

Neal

Guentchev

Arulalan

et al. 2022

Meteorological Applications

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A method is presented for deriving probabilistic medium‐range (1‐to‐2‐week) weather pattern forecasts for India. This method uses an existing set of 30 objectively derived daily weather patterns, which provide climatological representations for unique states in the large‐scale circulation over India. Weather pattern forecast probabilities are based on the number of ensemble members objectively assigned to each weather pattern. Two summer monsoon case studies illustrate the best use of the forecasting tool within medium‐range guidance, such as highlighting the most likely weather pattern transitions and relating these to the likelihood of weather impacts. Forecast skill is evident out to at least 10–15 days. Winter dry period weather patterns have the highest forecast skill, closely followed by retreating monsoon weather patterns. In contrast, monsoon onset and break monsoon weather patterns have the lowest forecast skill. Finally, a prototype weather pattern forecast climatology application is presented for use in highlighting when extreme rainfall is more likely than normal. This application is based on weather pattern empirical probabilities of threshold exceedances using a high‐resolution regional reanalysis. The transitional pre‐ and post‐monsoon seasons have the greatest variability in rainfall across all possible weather patterns, with a slight dip in variability during the main summer monsoon season. In contrast, very little variability across weather patterns is evident during the relatively dry winter months. This highlights the times of year when a climatology‐based weather pattern forecasting approach may have its greatest benefits over that of a basic daily climatology.

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“…Boorman et al (2010) attempted to compare modelling work with observed days of audible thunder over the UK observers, but the study was limited by a variety of factors, including the stations used changing with time, the density of stations being significantly different to the resolution of the climate models, and the surface stations being (naturally) limited to land areas. Wilkinson and Neal (2021) investigated the seasonal occurrence of lightning for different weather scenarios over the United Kingdom using Arrival Time Difference Network (ATDnet) data. Koehler (2020), Reap and Orville (1990), Czernecki et al (2016), and Changnon and co-workers (Changnon et al, 1988;Changnon, 2001) have all published work trying to draw together station data and lightning location network (LLN) data.…”

Section: Introductionmentioning

confidence: 99%

A gridded 30‐year days of thunder climatology for the United Kingdom

Stone

Horseman

Odams

et al. 2022

Quart J Royal Meteoro Soc

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Lightning and associated weather (e.g., hail, severe wind, tornado, and heavy rain) can cause severe impacts; therefore, it is important to understand how frequently thunderstorms occur and how the frequency might be changing with time. Published studies until now have been limited to relatively short time periods or extrapolated from low‐resolution surface data. This article presents the methods and results to combine long‐range lightning location network data (precise but inconsistent) with surface observations (less precise but more consistent) to generate a more consistent, more precise gridded days of thunder (DoTs) dataset for the United Kingdom. Both a 30‐year average (1990–2019) and rolling 10‐year averages are evaluated. For the 30‐year averages there is a maximum of ∼20$$ 20 $$ DoTs per year within the domain (over France) with a minimum of between 0 and 1 DoT per year (over the sea), with most of the UK land area having ∼10$$ 10 $$ DoTs per year. The summer shows the peak in DoTs relative to the other seasons. The 10‐year moving averages at either end of the 30 years allow for the trend in DoTs to be assessed. There has been a small (∼1$$ 1 $$ day) reduction in the average DoTs. There is a noteworthy north–south divide (at ∼54∘$$ 5{4}^{\circ } $$ N) with a small increase in the number of DoTs per year in the north of the UK and a small reduction in the south. The trends in 10‐year averages of DoTs are analysed for different regions of the United Kingdom (north land, south land, sea, land) over the four seasons. North land summer shows a small (∼0.5$$ 0.5 $$) increase in DoTs. All the other areas show a decrease.

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

Cited by 18 publications

References 57 publications

A regional lightning climatology of the UK and Ireland and sensitivity to alternative detection networks

A regional lightning climatology of the UK and Ireland and sensitivity to alternative detection networks

The application of predefined weather patterns over India within probabilistic medium‐range forecasting tools for high‐impact weather

A gridded 30‐year days of thunder climatology for the United Kingdom

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