JpGU-AGU Joint Meeting 2017

Presentation information

[EE] Poster

A (Atmospheric and Hydrospheric Sciences) » A-AS Atmospheric Sciences, Meteorology & Atmospheric Environment

[A-AS08] [EE] Towards integrated understandings of cloud and precipitation processes

Tue. May 23, 2017 1:45 PM - 3:15 PM Poster Hall (International Exhibition Hall HALL7)

convener:Kentaroh Suzuki(Atmosphere and Ocean Research Institute, University of Tokyo), Yukari Takayabu(Atmosphere and Ocean Research Institute, the University of Tokyo), Nagio Hirota(University of Tokyo), Tomoki Miyakawa(Atmosphere and Ocean Research Institute University of Tokyo)

[AAS08-P21] REVIEW OF CHARACTERISTICS OF ELECTRIC FIELD PRIOR TO LIGHTNING

*SRICHITRA S1, SEBIN SABU1, NORA ELIZABETH JOBY3,2, PREMLET B3 (1.TKM COLLEGE OF ENGINEERING KOLLAM, 2.NATIONAL INSTITUTE OF TECHNOLOGY CALICUT, 3.MES KOLLAM)

Keywords:Lightning, Electric field , Prior to strike

Abstract:A study on the atmospheric electric fields prior to lighting strike was conducted by means of literature survey and data analysis. Study of electric fields is an important tool of lightning research. Electric field mills are used to observe static atmospheric electric fields during fair weather and during storm conditions. Comparisons show significant changes in electric field due to an approaching storm or a thunderstorm. Attempts to comprehend the variations prior to and after a strike has been done by observatories all over and this paper focuses on identifying characteristic changes in atmospheric electric field prior to a lightning strike. The focus is on static electric field variations prior to strike and this points out to the significance of study of electric field varying from a fair weather scenario to generation of bipolar preliminary breakdown pulses which is defined as the dynamic electrical activity inside cloud before strike. It has been explained by means of BIL (Breakdown Intermediate Leader) model as proposed by Clarence and Malan. Simulation experiments done by Carlson and Liang are seen to reproduce the same characteristics as obtained from field data. This paper helps in identifying the characteristic change in atmospheric electric field prior to lightning strike can create a great advantage in lightning prediction.