Lightning fatalities over India: 1979–2011

Singh, Omvir; Singh, Jagdeep

doi:10.1002/met.1520

Cited by 92 publications

(46 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many hazardous phenomena occur with thunderstorms, such as strong gusts, lashing rain, hail and even tornadoes (Puranik and Karekar, 2004) and lightning flashes (Manohar et al, 2008;Nath et al, 2009;Kumar and Kamra, 2012a, b). These severe weather events cause extensive structural damages, destruction of crops, uprooting of trees and casualties (Singh and Singh, 2015;. Bhardwaj et al (2017) observed that about 80% of the total reported thunderstorm casualties in India occur during the pre-monsoon season.…”

Section: Introductionmentioning

confidence: 99%

Spatial and temporal analysis of thunderstorm and rainfall activity over India

Bhardwaj

Singh

2018

Atm

Self Cite

View full text Add to dashboard Cite

RESUMENLas tormentas eléctricas son uno de los fenómenos meteorológicos severos de mesoescala más devastadores, y desempeñan un papel relevante en la incidencia de precipitación en una región. Por ello, en el presente estudio se trató de identificar la relación entre días de tormenta (Thn), días de lluvia (Thr) y cantidad de la precipitación (Trr) en 294 estaciones meteorológicas distribuidas a lo largo de la India por medio de datos (normales climatológicas) publicados por el Departamento Meteorológico de la India (IMD, por sus siglas en inglés) para cuatro periodos: 1951-1980, 1961-1990, 1971-2000 y 1981-2010. El análisis mostró la existencia de una reducción drástica en la frecuencia de Thn, mientras que Thr y Trr mostraron un descenso leve. Se observó una correlación significativa entre las tres variables. El análisis mensual mostró un pico doble en la ocurrencia de Thn y un pico sencillo en la precipitación; sin embargo, se advirtió un intervalo de un mes entre la presentación de estos picos. Estos resultados demuestran que el monzón de verano de la India afecta de manera significativa la actividad de las tormentas eléctricas. El análisis estacional sugiere que Thn, Thr y Trr alcanzaron sus máximos durante la estación del monzón y sus mínimos durante el invierno. Por otra parte, se ha demostrado la existencia de una relación negativa entre Thn y Thr, y Thn y Trr durante el monzón, anomalía que puede deberse a la temperatura decreciente en la India durante dicha estación. Adicionalmente, el patrón espacial mensual y estacional de la ocurrencia de Thn, Thr y Trr permanece casi inalterado en el periodo . No obstante, se observó una disminución drástica en la frecuencia de Thn en los periodos subsiguientes en todo el país. De manera similar, se percibió una leve disminución en la frecuencia de Thr y Trr sobre la India, excepto en el noreste, que exhibe una tendencia al alza en la precipitación. Se ha encontrado que el índice Thn/Thr (R) alcanza su máximo en la temporada previa al monzón, mientras que el índice Trr/Thn alcanza su máximo durante la temporada del monzón. El análisis regional de Thn, Thr y Trr muestra una amplia gama de variaciones en la ocurrencia de estos patrones a lo largo del año. Se considera que los resultados de este estudio serán de utilidad para los meteorólogos, pilotos aviadores, agricultores y planificadores. ABSTRACTThunderstorms are one of the most devastating mesoscale severe weather phenomena, which play an important role in the occurrence of rainfall activity over a region. Therefore, in the present study an attempt has been made to identify the relationship between thunderstorm days (Thn), rainy days (Thr) and rainfall amounts (Trr) for 294 meteorological stations spreading over India, by means of published data (climatological normals) from the India Meteorological Department (IMD) for four periods, 1951-1980, 1961-1990, 1971-2000, and 1981-2010. The analysis has revealed a sharp decrease in the frequency of Thn, while Thr and Trr showed a slight decline. A significant correlat...

show abstract

Section: Introductionmentioning

confidence: 99%

Spatial and temporal analysis of thunderstorm and rainfall activity over India

Bhardwaj

Singh

2018

Atm

Self Cite

View full text Add to dashboard Cite

show abstract

“…Moreover, the publication is unique and the only kind of dataset of its type and thus must be used for this type of analysis. Accordingly, this database has been used earlier for comprehensive studies on extreme weather events (De et al , ), floods (Singh & Kumar, ) and lightning (Singh & Singh, ) in the Indian region.…”

Section: Database and Methodologymentioning

confidence: 99%

Spatial and temporal variations in thunderstorm casualties over India

Bhardwaj

Singh

Kumar

2017

Singap J Trop Geogr

Self Cite

View full text Add to dashboard Cite

Thunderstorms are one of the most dangerous convective weather events. Despite the recent advances in prediction of convective storms worldwide, thousands of casualties occur annually. In the present study, the authors highlight specifically, thunderstorm‐related casualties reported in India from 1978–2012. Analysis of long‐term data have revealed about 16 308 casualties resulting from 1381 thunderstorm events with an average of 465 casualties occurring annually. The maximum number of casualties were concentrated in north‐eastern and central north‐eastern states. About 80 per cent of total casualties were recorded in West Bengal (23 per cent), Assam (20 per cent), Orissa (14 per cent), Bihar (13 per cent) and Jharkhand (8 per cent) states. The national casualties rate per million population per year and casualties density standardized by area has been found to be 0.50 and 5.07, respectively. Male casualties were found to be more prominent than female and children casualties, probably due to the larger proportion of males performing their work outdoors. The number of thunderstorm events and casualties was observed to be highest during pre‐monsoon season and lowest during winter. It is believed that the findings from this study will help policy makers to draw strategies to cope with the perils of thunderstorms.

show abstract

“…Among these, Maharashtra ranks 1, West Bengal 2, Uttar Pradesh 3, Kerala 4, and Karnataka 5 (Singh and Singh, 2015). The population densities in Maharashtra, West Bengal, Uttar Pradesh, Kerala, and Karnataka are 365, 1029, 828, 859, and 319 per sq km.…”

Section: Increasing Evaporationmentioning

confidence: 99%

“…As the sun heats up the ground in the warm season, the (Singh and Singh, 2015). rapidly increasing environmental lapse rate (5 K/km) surpasses the dry adiabatic cooling rate (9.8 K/km) in a shallow layer that becomes turbulent.…”

Section: Cumulonimbus Cloud Formationmentioning

confidence: 99%