Comparison of simulating visibility using XGBoost and IMPROVE method: a case study in East China
The prediction accuracy of atmospheric visibility significantly impacts daily life. However, there is a relative scarcity of research on post-processing methods for visibility obtained from the WRF-Chem atmospheric chemistry model results. In order to explore a more accurate method for visibility ca...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Environmental Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2024.1534113/full |
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| author | Xin Zhang Yue Wang Zibo Zhuang Yuxi Liu Chengduo Yuan Lei Su Jingyuan Shao Pak-Wai Chan |
| author_facet | Xin Zhang Yue Wang Zibo Zhuang Yuxi Liu Chengduo Yuan Lei Su Jingyuan Shao Pak-Wai Chan |
| author_sort | Xin Zhang |
| collection | DOAJ |
| description | The prediction accuracy of atmospheric visibility significantly impacts daily life. However, there is a relative scarcity of research on post-processing methods for visibility obtained from the WRF-Chem atmospheric chemistry model results. In order to explore a more accurate method for visibility calculation, we conducted a study on the meteorological conditions in the East China region during a heavy pollution period from October 1 to 23 in the year of 2022. The meteorological data were processed using both the XGBoost (XGB) model and the IMPROVE to calculate visibility. The results indicate that XGB outperforms the IMPROVE in various aspects. The visibility improved from a correlation of 0.56–0.71 with the use of XGB. And in comparison with the IMPROVE equation, XGB demonstrated a statistically significant reduction in RMSE by 1.96 km. Even in regions where the IMPROVE performs poorly, XGB demonstrates superior performance. In regions where the correlation simulated by the IMPROVE equation is less than 0.2 (Anqing and Nanyang), XGB still performs well, achieving correlations of 0.69 (Anqing) and 0.68 (Nanyang). Throughout the entire study period, the average visibility results obtained by XGB deviate by only 0.07 km from the observed values. These findings underscore the importance of incorporating the XGBoost model into WRF-Chem visibility simulations, as it significantly improves the accuracy of visibility predictions. |
| format | Article |
| id | doaj-art-6ed29e9523e9441191699c031993099f |
| institution | Kabale University |
| issn | 2296-665X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Environmental Science |
| spelling | doaj-art-6ed29e9523e9441191699c031993099f2025-01-20T07:19:56ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2025-01-011210.3389/fenvs.2024.15341131534113Comparison of simulating visibility using XGBoost and IMPROVE method: a case study in East ChinaXin Zhang0Yue Wang1Zibo Zhuang2Yuxi Liu3Chengduo Yuan4Lei Su5Jingyuan Shao6Pak-Wai Chan7Flight Academy of Civil Aviation University of China, Tianjin, ChinaDepartment of Safety Science and Engineering, Civil Aviation University of China, Tianjin, ChinaAviation Meteorological Research Institute, Civil Aviation University of China, Tianjin, ChinaState Environmental Protection Key Laboratory of Environmental Pollution and Greenhouse Gases Co-control, Chinese Academy of Environmental Planning, Beijing, ChinaDepartment of Flight Area Management, Harbin International Airport Co., Ltd., Harbin, ChinaDepartment of Safety Science and Engineering, Civil Aviation University of China, Tianjin, ChinaFlight Academy of Civil Aviation University of China, Tianjin, ChinaHong Kong Observatory, Hong Kong, Hong Kong SAR, ChinaThe prediction accuracy of atmospheric visibility significantly impacts daily life. However, there is a relative scarcity of research on post-processing methods for visibility obtained from the WRF-Chem atmospheric chemistry model results. In order to explore a more accurate method for visibility calculation, we conducted a study on the meteorological conditions in the East China region during a heavy pollution period from October 1 to 23 in the year of 2022. The meteorological data were processed using both the XGBoost (XGB) model and the IMPROVE to calculate visibility. The results indicate that XGB outperforms the IMPROVE in various aspects. The visibility improved from a correlation of 0.56–0.71 with the use of XGB. And in comparison with the IMPROVE equation, XGB demonstrated a statistically significant reduction in RMSE by 1.96 km. Even in regions where the IMPROVE performs poorly, XGB demonstrates superior performance. In regions where the correlation simulated by the IMPROVE equation is less than 0.2 (Anqing and Nanyang), XGB still performs well, achieving correlations of 0.69 (Anqing) and 0.68 (Nanyang). Throughout the entire study period, the average visibility results obtained by XGB deviate by only 0.07 km from the observed values. These findings underscore the importance of incorporating the XGBoost model into WRF-Chem visibility simulations, as it significantly improves the accuracy of visibility predictions.https://www.frontiersin.org/articles/10.3389/fenvs.2024.1534113/fullvisibility simulationXGBoostIMPROVE equationWRF-Chem modelmachine learningatmospheric chemistry |
| spellingShingle | Xin Zhang Yue Wang Zibo Zhuang Yuxi Liu Chengduo Yuan Lei Su Jingyuan Shao Pak-Wai Chan Comparison of simulating visibility using XGBoost and IMPROVE method: a case study in East China Frontiers in Environmental Science visibility simulation XGBoost IMPROVE equation WRF-Chem model machine learning atmospheric chemistry |
| title | Comparison of simulating visibility using XGBoost and IMPROVE method: a case study in East China |
| title_full | Comparison of simulating visibility using XGBoost and IMPROVE method: a case study in East China |
| title_fullStr | Comparison of simulating visibility using XGBoost and IMPROVE method: a case study in East China |
| title_full_unstemmed | Comparison of simulating visibility using XGBoost and IMPROVE method: a case study in East China |
| title_short | Comparison of simulating visibility using XGBoost and IMPROVE method: a case study in East China |
| title_sort | comparison of simulating visibility using xgboost and improve method a case study in east china |
| topic | visibility simulation XGBoost IMPROVE equation WRF-Chem model machine learning atmospheric chemistry |
| url | https://www.frontiersin.org/articles/10.3389/fenvs.2024.1534113/full |
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