{"title":"Using Machine Learning Methods to Develop an Algorithm for Recognizing a Risk of Waterspout Occurrence off the Black Sea Coast of Russia","authors":"O. V. Kalmykova","doi":"10.3103/s1068373924040101","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Every year about 50 waterspouts occur over the sea off the Black Sea coast of Russia. Over the past few years, the cases of waterspouts have occurred in the immediate vicinity of the coast with their subsequent destruction. The vortex destruction is often accompanied by short-term wind strengthening up to storm levels. The present study solves the problem of nowcasting the Black Sea waterspouts (building a detailed forecast of their formation for the next 2–6 hours) using machine learning methods. Learning by precedents is considered based on the labeled dataset of the radar characteristics of convective systems with and without waterspouts, models for classifying systems in terms of the risk of waterspout occurrence are constructed. The testing of the models showed that it is fundamentally possible to use them to diagnose systems with already formed waterspouts, as well as to identify the risk of waterspouts in advance (within two hours).</p>","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.3103/s1068373924040101","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Every year about 50 waterspouts occur over the sea off the Black Sea coast of Russia. Over the past few years, the cases of waterspouts have occurred in the immediate vicinity of the coast with their subsequent destruction. The vortex destruction is often accompanied by short-term wind strengthening up to storm levels. The present study solves the problem of nowcasting the Black Sea waterspouts (building a detailed forecast of their formation for the next 2–6 hours) using machine learning methods. Learning by precedents is considered based on the labeled dataset of the radar characteristics of convective systems with and without waterspouts, models for classifying systems in terms of the risk of waterspout occurrence are constructed. The testing of the models showed that it is fundamentally possible to use them to diagnose systems with already formed waterspouts, as well as to identify the risk of waterspouts in advance (within two hours).
期刊介绍：
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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