Lightning Risk Warning Method Using Atmospheric Electric Field Based on EEWT-ASG and Morpho
The current methods for lightning risk warnings that are based on atmospheric electric field (AEF) data have a tendency to rely on single features, which results in low robustness and efficiency. Additionally, there is a lack of research on canceling warning signals, contributing to the high false a...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/14/6/1002 |
| _version_ | 1797596160081264640 |
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| author | Xiang Li Ling Yang Qiyuan Yin Zhipeng Yang Fangcong Zhou |
| author_facet | Xiang Li Ling Yang Qiyuan Yin Zhipeng Yang Fangcong Zhou |
| author_sort | Xiang Li |
| collection | DOAJ |
| description | The current methods for lightning risk warnings that are based on atmospheric electric field (AEF) data have a tendency to rely on single features, which results in low robustness and efficiency. Additionally, there is a lack of research on canceling warning signals, contributing to the high false alarm rate (FAR) of these methods. To overcome these limitations, this study proposes a lightning risk warning method that incorporates enhanced empirical Wavelet transform-Adaptive Savitzky–Golay filter (EEWT-ASG) and one-dimensional morphology, using time-frequency domain features obtained through the Wavelet transform (WT). The proposed method achieved a probability of detection (POD) of 77.11%, miss alarm rate (MAR) of 22.89%, FAR of 40.19%, and critical success index (CSI) of 0.51, as evaluated on 83 lightning events. This method can issue a warning signal up to 22 min in advance for lightning processes. |
| first_indexed | 2024-03-11T02:46:40Z |
| format | Article |
| id | doaj.art-4a35c36851974bdf9c20a249cf399475 |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-11T02:46:40Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-4a35c36851974bdf9c20a249cf3994752023-11-18T09:14:52ZengMDPI AGAtmosphere2073-44332023-06-01146100210.3390/atmos14061002Lightning Risk Warning Method Using Atmospheric Electric Field Based on EEWT-ASG and MorphoXiang Li0Ling Yang1Qiyuan Yin2Zhipeng Yang3Fangcong Zhou4College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, ChinaCollege of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, ChinaKey Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province, Haikou 570100, ChinaCollege of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, ChinaKey Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province, Haikou 570100, ChinaThe current methods for lightning risk warnings that are based on atmospheric electric field (AEF) data have a tendency to rely on single features, which results in low robustness and efficiency. Additionally, there is a lack of research on canceling warning signals, contributing to the high false alarm rate (FAR) of these methods. To overcome these limitations, this study proposes a lightning risk warning method that incorporates enhanced empirical Wavelet transform-Adaptive Savitzky–Golay filter (EEWT-ASG) and one-dimensional morphology, using time-frequency domain features obtained through the Wavelet transform (WT). The proposed method achieved a probability of detection (POD) of 77.11%, miss alarm rate (MAR) of 22.89%, FAR of 40.19%, and critical success index (CSI) of 0.51, as evaluated on 83 lightning events. This method can issue a warning signal up to 22 min in advance for lightning processes.https://www.mdpi.com/2073-4433/14/6/1002atmospheric electric field (AEF)lightning risk warningenhanced empirical wavelet transform-adaptive Savitzky–Golay filter (EEWT-ASG)one-dimensional morphologywavelet transform (WT) |
| spellingShingle | Xiang Li Ling Yang Qiyuan Yin Zhipeng Yang Fangcong Zhou Lightning Risk Warning Method Using Atmospheric Electric Field Based on EEWT-ASG and Morpho Atmosphere atmospheric electric field (AEF) lightning risk warning enhanced empirical wavelet transform-adaptive Savitzky–Golay filter (EEWT-ASG) one-dimensional morphology wavelet transform (WT) |
| title | Lightning Risk Warning Method Using Atmospheric Electric Field Based on EEWT-ASG and Morpho |
| title_full | Lightning Risk Warning Method Using Atmospheric Electric Field Based on EEWT-ASG and Morpho |
| title_fullStr | Lightning Risk Warning Method Using Atmospheric Electric Field Based on EEWT-ASG and Morpho |
| title_full_unstemmed | Lightning Risk Warning Method Using Atmospheric Electric Field Based on EEWT-ASG and Morpho |
| title_short | Lightning Risk Warning Method Using Atmospheric Electric Field Based on EEWT-ASG and Morpho |
| title_sort | lightning risk warning method using atmospheric electric field based on eewt asg and morpho |
| topic | atmospheric electric field (AEF) lightning risk warning enhanced empirical wavelet transform-adaptive Savitzky–Golay filter (EEWT-ASG) one-dimensional morphology wavelet transform (WT) |
| url | https://www.mdpi.com/2073-4433/14/6/1002 |
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