Publication:
Lightning peak current estimation using a system identification approach

Simple item page
dc.citedby0
dc.contributor.authorWern T.L.T.en_US
dc.contributor.authorMukerjee R.N.en_US
dc.contributor.authorid11739827500en_US
dc.contributor.authorid7003827066en_US
dc.date.accessioned2023-12-28T08:57:43Z
dc.date.available2023-12-28T08:57:43Z
dc.date.issued2006
dc.description.abstractA system identification-based lightning peak current estimation algorithm using upper-air radiosonde observations is developed. The preceding convective and precipitative process leading to thunder cloud formation followed by the cloud electrification and the leader processes together with return stroke and the discharge process, is identified by considering it as a deterministic dynamic system, whose undisturbed and unmeasurable output signal - the lightning peak current, is contaminated with a stochastic disturbance. The model parameters determined thus, are used to predict the likely temporal lightning return stroke peak current magnitudes. Two alternative parametric estimation models namely Autoregressive with Exogeneous Input (ARX) and Autoregressive with Moving-Average Exogeneous Input (ARMAX) are used to estimate model parameters of the pilot study area and predict the likely lightning return stroke peak current in each case. The relative performances of the models are compared to determine the best model for application in 12-hour and 24-hour ahead predictions. For a short-term (12 hour) prediction, ARMAX2921 giving a best fit of 78.8429% turns out to be the most suitable model. For a longer (24 hour) prediction, the ARX291, giving a best fit of 75.0181% emerges to be the suitable model. These preliminary results indicate that lightning peak current may be estimated to a good performance using upper-air radiosonde observations. � Springer-Verlag/Wien 2006.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/s00703-005-0135-x
dc.identifier.epage44
dc.identifier.issue01/04/2023
dc.identifier.scopus2-s2.0-31044441880
dc.identifier.spage25
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-31044441880&doi=10.1007%2fs00703-005-0135-x&partnerID=40&md5=4a4607cf43c11e5ef9e9e915aaa9776f
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/29804
dc.identifier.volume91
dc.pagecount19
dc.sourceScopus
dc.sourcetitleMeteorology and Atmospheric Physics
dc.subjectatmospheric electricity
dc.subjectlightning
dc.subjectthundercloud
dc.titleLightning peak current estimation using a system identification approachen_US
dc.typeArticleen_US
dspace.entity.typePublication
Files
Collections
SCOPUS