Neural Network for Lightning Forecasting in Southeastern Brazil
DOI:
https://doi.org/10.5902/2179460X13721Keywords:
Lightning, forecasting, MM5 model, neural network.Abstract
This paper introduces a lightning forecasting system using Neural Networks (NN) based on correlations betweencloud-to-ground (CG) lightning flash data and meteorological variables obtained from MM5 (Fifth-GenerationPenn State/NCAR Mesoscale Model) simulations in southeastern Brazil. Besides the area of nineteen high densitylightning subregions selected from non-severe thunderstorms cases, the following model parameters were also usedas inputs for the NN: divergence at 850 hPa and 200 hPa, temperature advection at 500 hPa, vertical velocity at500 hPa, and water vapor-mixing ratio at the surface and 850 hPa. The target output of the neural system was thenumber of CG lightning flashes that would occur one hour in advance. Four cases, not previously trained, of highdensity lightning subregions were used to test the system efficiency. Although the testing cases were sufficientlydifferent, a case with no occurrence of lightning has also been included in order to not introduce any bias on theanalysis. The results of the lightning forecasting were promising, indicating that the NN technique associated withmodel variables from numerical simulations can be an efficient tool for predicting flash occurrence appropriately.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
To access the DECLARATION AND TRANSFER OF COPYRIGHT AUTHOR’S DECLARATION AND COPYRIGHT LICENSE click here.
Ethical Guidelines for Journal Publication
The Ciência e Natura journal is committed to ensuring ethics in publication and quality of articles.
Conformance to standards of ethical behavior is therefore expected of all parties involved: Authors, Editors, Reviewers, and the Publisher.
In particular,
Authors: Authors should present an objective discussion of the significance of research work as well as sufficient detail and references to permit others to replicate the experiments. Fraudulent or knowingly inaccurate statements constitute unethical behavior and are unacceptable. Review Articles should also be objective, comprehensive, and accurate accounts of the state of the art. The Authors should ensure that their work is entirely original works, and if the work and/or words of others have been used, this has been appropriately acknowledged. Plagiarism in all its forms constitutes unethical publishing behavior and is unacceptable. Submitting the same manuscript to more than one journal concurrently constitutes unethical publishing behavior and is unacceptable. Authors should not submit articles describing essentially the same research to more than one journal. The corresponding Author should ensure that there is a full consensus of all Co-authors in approving the final version of the paper and its submission for publication.
Editors: Editors should evaluate manuscripts exclusively on the basis of their academic merit. An Editor must not use unpublished information in the editor's own research without the express written consent of the Author. Editors should take reasonable responsive measures when ethical complaints have been presented concerning a submitted manuscript or published paper.
Reviewers: Any manuscripts received for review must be treated as confidential documents. Privileged information or ideas obtained through peer review must be kept confidential and not used for personal advantage. Reviewers should be conducted objectively, and observations should be formulated clearly with supporting arguments, so that Authors can use them for improving the paper. Any selected Reviewer who feels unqualified to review the research reported in a manuscript or knows that its prompt review will be impossible should notify the Editor and excuse himself from the review process. Reviewers should not consider manuscripts in which they have conflicts of interest resulting from competitive, collaborative, or other relationships or connections with any of the authors, companies, or institutions connected to the papers.
