The Role of Instability Indices in Forecasting Thunderstorm and Non-Thunderstorm Days across Six Cities in India
Thunderstorms are one of the most damaging natural hazards demanding in-depth understanding and prediction. These convective systems form in an unstable environment which is quantitatively expressed in terms of instability indices. These indices are studied over six locations across the Indian landm...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Climate |
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| Online Access: | https://www.mdpi.com/2225-1154/11/1/14 |
| _version_ | 1797444164212752384 |
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| author | Kopal Arora Kamaljit Ray Suresh Ram Rajeev Mehajan |
| author_facet | Kopal Arora Kamaljit Ray Suresh Ram Rajeev Mehajan |
| author_sort | Kopal Arora |
| collection | DOAJ |
| description | Thunderstorms are one of the most damaging natural hazards demanding in-depth understanding and prediction. These convective systems form in an unstable environment which is quantitatively expressed in terms of instability indices. These indices are studied over six locations across the Indian landmass in an attempt to predict thunderstorm activity on any given day. A combination of multiple regression, logistic regression, and range analysis provides new insight into the prediction of these storms. A supervised machine learning-based logistic regression model is developed in this study for thunderstorm prediction over Patna and can be further extended for operational forecasting of Thunderstorms over the region. Critical thresholds for the instability indices are determined over the considered locations providing valuable insight into the domain of Thunderstorm prediction |
| first_indexed | 2024-03-09T13:07:36Z |
| format | Article |
| id | doaj.art-664206b41b8548608ac6ddaa3593c187 |
| institution | Directory Open Access Journal |
| issn | 2225-1154 |
| language | English |
| last_indexed | 2024-03-09T13:07:36Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Climate |
| spelling | doaj.art-664206b41b8548608ac6ddaa3593c1872023-11-30T21:45:54ZengMDPI AGClimate2225-11542023-01-011111410.3390/cli11010014The Role of Instability Indices in Forecasting Thunderstorm and Non-Thunderstorm Days across Six Cities in IndiaKopal Arora0Kamaljit Ray1Suresh Ram2Rajeev Mehajan3Ministry of Earth Sciences, Delhi 110059, IndiaMinistry of Earth Sciences, Delhi 110059, IndiaMinistry of Earth Sciences, Delhi 110059, IndiaScience and Engineering Research Board, Department of Science and Technology, New Delhi 110070, IndiaThunderstorms are one of the most damaging natural hazards demanding in-depth understanding and prediction. These convective systems form in an unstable environment which is quantitatively expressed in terms of instability indices. These indices are studied over six locations across the Indian landmass in an attempt to predict thunderstorm activity on any given day. A combination of multiple regression, logistic regression, and range analysis provides new insight into the prediction of these storms. A supervised machine learning-based logistic regression model is developed in this study for thunderstorm prediction over Patna and can be further extended for operational forecasting of Thunderstorms over the region. Critical thresholds for the instability indices are determined over the considered locations providing valuable insight into the domain of Thunderstorm predictionhttps://www.mdpi.com/2225-1154/11/1/14thunderstormsmultiple linear regressionlogistic regressioninstability indicesthunderstorm forecastingsupervised machine learning |
| spellingShingle | Kopal Arora Kamaljit Ray Suresh Ram Rajeev Mehajan The Role of Instability Indices in Forecasting Thunderstorm and Non-Thunderstorm Days across Six Cities in India Climate thunderstorms multiple linear regression logistic regression instability indices thunderstorm forecasting supervised machine learning |
| title | The Role of Instability Indices in Forecasting Thunderstorm and Non-Thunderstorm Days across Six Cities in India |
| title_full | The Role of Instability Indices in Forecasting Thunderstorm and Non-Thunderstorm Days across Six Cities in India |
| title_fullStr | The Role of Instability Indices in Forecasting Thunderstorm and Non-Thunderstorm Days across Six Cities in India |
| title_full_unstemmed | The Role of Instability Indices in Forecasting Thunderstorm and Non-Thunderstorm Days across Six Cities in India |
| title_short | The Role of Instability Indices in Forecasting Thunderstorm and Non-Thunderstorm Days across Six Cities in India |
| title_sort | role of instability indices in forecasting thunderstorm and non thunderstorm days across six cities in india |
| topic | thunderstorms multiple linear regression logistic regression instability indices thunderstorm forecasting supervised machine learning |
| url | https://www.mdpi.com/2225-1154/11/1/14 |
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