A ten-year analysis of cloud-to-ground lightning activity over the Eastern Mediterranean region

Galanaki, Elissavet; Kotroni, Vassiliki; Lagouvardos, K.; Argiriou, Athanassios A.

doi:10.1016/j.atmosres.2015.07.008

Cited by 65 publications

(60 citation statements)

References 56 publications

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“…Although several real‐time lightning detection systems (e.g., Nash et al [] for ATDNET; Betz et al [] for LINET; Lagouvardos et al [], Pohjola and Mäkelä [], Galanaki et al [], Poelman et al [], and Schulz et al [] for EUCLID; and Karagiannidis et al [] for ZEUS) are nowadays able to determine the impact location of lightning with high accuracy, their occurrence in short‐range meteorological forecasting is still affected by many sources of uncertainty [ McCaul et al , , Dahl et al , ]. Different algorithms for the prediction of the total lightning spatio‐temporal evolution have been considered for severe weather detection, resulting in the development of valuable tools for the warning decision‐making process of forecasters.…”

Section: Introductionmentioning

confidence: 99%

Lightning Potential Index performances in multimicrophysical cloud‐resolving simulations of a back‐building mesoscale convective system: The Genoa 2014 event

et al. 2017

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Severe weather events are responsible for hundreds of fatalities and millions of euros of damage every year on the Mediterranean basin. Lightning activity is a characteristic phenomenon of severe weather and often accompanies torrential rainfall, which, under certain conditions like terrain type, slope, drainage, and soil saturation, may turn into flash flood. Building on the existing relationship between significant lightning activity and deep convection and precipitation, the performance of the Lightning Potential Index, as a measure of the potential for charge generation and separation that leads to lightning occurrence in clouds, is here evaluated for the V‐shape back‐building Mesoscale Convective System which hit Genoa city (Italy) in 2014. An ensemble of Weather Research and Forecasting simulations at cloud‐permitting grid spacing (1 km) with different microphysical parameterizations is performed and compared to the available observational radar and lightning data. The results allow gaining a deeper understanding of the role of lightning phenomena in the predictability of V‐shape back‐building Mesoscale Convective Systems often producing flash flood over western Mediterranean complex topography areas. Moreover, they support the relevance of accurate lightning forecasting for the predictive ability of these severe events.

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Section: Introductionmentioning

confidence: 99%

Lightning Potential Index performances in multimicrophysical cloud‐resolving simulations of a back‐building mesoscale convective system: The Genoa 2014 event

et al. 2017

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“…Price () showed a close link between upper tropospheric water vapour variability and global lightning activity. Convective available potential energy (CAPE), an indicator of atmospheric instability, was evaluated to reveal its influence on lightning in various settings (Williams and Renno, ; Romps et al ., ; Galanaki et al ., ). These studies demonstrated an increase of lightning activity with increasing CAPE.…”

Section: Introductionmentioning

confidence: 99%

Lightning activity associated with precipitation and CAPE over Bangladesh

Dewan

Ongee

Rafiuddin

et al. 2017

Intl Journal of Climatology

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Satellite‐derived lightning data for 17 years (1998–2014) were used to evaluate the relation between environmental factors and lightning activity over the Bangladesh landmass. Time series convective available potential energy (CAPE) data were extracted from ERA‐40 reanalysis data while total and convective rainfalls were obtained from Tropical Rainfall Measuring Mission's monthly products. In addition, the product of CAPE and precipitation was computed and used as an additional variable. Three timescales – monthly, seasonal and annual – were utilized to determine the influence of precipitation and CAPE on lightning activity. The results indicated that CAPE stands out as an important variable at all of these timescales for predicting the occurrence of lightning. The correlation coefficient (r) between CAPE and lightning activity was found to be 0.902 (monthly), 0.703 (pre‐monsoon), 0.550 (monsoon) and 0.702 (annual), respectively. Total rain showed strong positive correlation with lightning on monthly scale (r = 0.734) and in the pre‐monsoon season (r = 0.701). However, such relationship was moderate during monsoon (r = 0.455). In contrast, convective rain showed slightly higher correlation during monsoon (r = 0.587) compared with that of pre‐monsoon season (r = 0.532). Because of strong seasonality in the data, convective rain did not exhibit strong relationship on annual scale (r = 0.227). The product variable (e.g. CAPE × precipitation) showed significant correlation on monthly (r = 0.895) and seasonal scales (r = 0.818 during pre‐monsoon and 0.686 in monsoon) but its influence appears to diminish on a longer timescale (r = 0.375). Spatial maps of correlation coefficient revealed significant positive correlation along relatively drier northern parts of Bangladesh. As lightning‐related fatality is on the rise, this study, first of its kind, is expected to inform public policy and provide information necessary for effective management of this atmospheric phenomenon to save lives and property in Bangladesh.

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“…Many studies have been devoted to the study of the relation of lightning with underlying physiographic characteristics (Soriano et al 2005, Mazarakis et al 2008, Goswami et al 2010, Galanaki et al 2015 and found the dependence of lightning with orography but most importantly with steep topographic gradients, that favour further uplift of unstable air masses. A number of studies have been also devoted to the investigation of the atmospheric factors controlling lightning activity and many authors highlighted a high correlation of lightning activity with the convective available potential energy (Mazarakis et al 2008, Ziv et al 2009, Goswami et al 2010, Pawar et al 2012, Galanaki et al 2015. Although the sea surface temperature (SST) is a crucial parameter implicated in the air-sea interaction and strongly related to instability, little work has been done to investigate the possible relationship of lightning with SST.…”

Section: Introductionmentioning

confidence: 99%

Lightning in the Mediterranean and its relation with sea-surface temperature

Kotroni

Lagouvardos

2016

Environ. Res. Lett.

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Here we present the analysis of lightning activity over the Mediterranean, based on a 10 year long dataset (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014) provided by the ZEUS long-range lightning detection system. The major hotspots of lightning activity are identified, with a clear predominance during the warm period of the year over land in the vicinity of the major topographic features of the area. Special emphasis is also given on the discussion of the seasonal distribution of lightning. In addition, we investigate the relationship of lightning with sea-surface temperature, obtained by high-resolution satellite measurements and we conclude that the number of lightning strokes is positively correlated with the sea-surface temperature during autumn when also the maximum lightning activity over the sea is depicted. We suggest that higher sea surface temperature further destabilises the lower tropospheric layers, enhancing thus convection and therefore lightning.

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A ten-year analysis of cloud-to-ground lightning activity over the Eastern Mediterranean region

Cited by 65 publications

References 56 publications

Lightning Potential Index performances in multimicrophysical cloud‐resolving simulations of a back‐building mesoscale convective system: The Genoa 2014 event

Lightning Potential Index performances in multimicrophysical cloud‐resolving simulations of a back‐building mesoscale convective system: The Genoa 2014 event

Lightning activity associated with precipitation and CAPE over Bangladesh

Lightning in the Mediterranean and its relation with sea-surface temperature

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