Characteristics of large-scale atmospheric circulation patterns conducive to severe spring and winter wind events over beijing in china based on a machine learning categorizing method
Severe wind events which occur in the metropolis of Beijing in China bring major catastrophes. Characteristics of severe winter and spring wind events over Beijing during the past 40 years have been analyzed. An artificial intelligence-based method is adopted to categorize the favorable large-scale...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-09-01
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| Series: | Frontiers in Earth Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2022.998108/full |
| _version_ | 1828240471438131200 |
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| author | Wei Zhao Wei Zhao Cui Hao Jie Cao Xiaoqing Lan Yan Huang |
| author_facet | Wei Zhao Wei Zhao Cui Hao Jie Cao Xiaoqing Lan Yan Huang |
| author_sort | Wei Zhao |
| collection | DOAJ |
| description | Severe wind events which occur in the metropolis of Beijing in China bring major catastrophes. Characteristics of severe winter and spring wind events over Beijing during the past 40 years have been analyzed. An artificial intelligence-based method is adopted to categorize the favorable large-scale circulation patterns and dominant weather systems. Four categories are concluded and compared to each other in terms of distributions of geopotential height at 500 hPa, temperature at 500 hPa, sea level pressure and their corresponding anomalies in 1979–2019. It is found that the first category (T1) which is dominated by strong cold trough at upper levels with strong cold-core high locating at surface is the most conducive circulation pattern, while the fourth category (T4) which is controlled by weak trough and strong ridge with strong low cyclone at surface is the least one. The second and third categories, represented by T2 and T3, are under the control of strong cold trough and warm ridge at upper levels with weak high at surface, and of weak trough and strong ridge with strong low cyclone at surface, respectively. Characteristics and differences under different backgrounds of global temperatures are analyzed by separating the past 40years into two distinct periods. The decreasing trends of intensities of the trough and ridge, the temperature at 500hPa, together with the surface systems, are found to be responsible for the decrease in severe wind events in T1, T2 and T3 in the last 20 years, while T4 is distinct to the other three categories with little change in its circulation pattern, and thus continues contributing to the severe wind events over Beijing. The results found in this study with the usage of an AI-based algorithm will benefit for the operational forecasting for extreme wind events over Beijing. |
| first_indexed | 2024-04-12T21:41:52Z |
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| id | doaj.art-1c12e8ee97a146e0b573ee105ef90542 |
| institution | Directory Open Access Journal |
| issn | 2296-6463 |
| language | English |
| last_indexed | 2024-04-12T21:41:52Z |
| publishDate | 2022-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Earth Science |
| spelling | doaj.art-1c12e8ee97a146e0b573ee105ef905422022-12-22T03:15:44ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632022-09-011010.3389/feart.2022.998108998108Characteristics of large-scale atmospheric circulation patterns conducive to severe spring and winter wind events over beijing in china based on a machine learning categorizing methodWei Zhao0Wei Zhao1Cui Hao2Jie Cao3Xiaoqing Lan4Yan Huang5Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters and Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, ChinaBeijing Meteorological Service, Beijing, ChinaBeijing Meteorological Service, Beijing, ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters and Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, ChinaCenter for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, ChinaNational Meteorological Service Center, China Meteorological Administration, Beijing, ChinaSevere wind events which occur in the metropolis of Beijing in China bring major catastrophes. Characteristics of severe winter and spring wind events over Beijing during the past 40 years have been analyzed. An artificial intelligence-based method is adopted to categorize the favorable large-scale circulation patterns and dominant weather systems. Four categories are concluded and compared to each other in terms of distributions of geopotential height at 500 hPa, temperature at 500 hPa, sea level pressure and their corresponding anomalies in 1979–2019. It is found that the first category (T1) which is dominated by strong cold trough at upper levels with strong cold-core high locating at surface is the most conducive circulation pattern, while the fourth category (T4) which is controlled by weak trough and strong ridge with strong low cyclone at surface is the least one. The second and third categories, represented by T2 and T3, are under the control of strong cold trough and warm ridge at upper levels with weak high at surface, and of weak trough and strong ridge with strong low cyclone at surface, respectively. Characteristics and differences under different backgrounds of global temperatures are analyzed by separating the past 40years into two distinct periods. The decreasing trends of intensities of the trough and ridge, the temperature at 500hPa, together with the surface systems, are found to be responsible for the decrease in severe wind events in T1, T2 and T3 in the last 20 years, while T4 is distinct to the other three categories with little change in its circulation pattern, and thus continues contributing to the severe wind events over Beijing. The results found in this study with the usage of an AI-based algorithm will benefit for the operational forecasting for extreme wind events over Beijing.https://www.frontiersin.org/articles/10.3389/feart.2022.998108/fullSOM methodlarge-scale circulationsynoptic weather systemglobal warmingsevere wind event in spring and winter seasons |
| spellingShingle | Wei Zhao Wei Zhao Cui Hao Jie Cao Xiaoqing Lan Yan Huang Characteristics of large-scale atmospheric circulation patterns conducive to severe spring and winter wind events over beijing in china based on a machine learning categorizing method Frontiers in Earth Science SOM method large-scale circulation synoptic weather system global warming severe wind event in spring and winter seasons |
| title | Characteristics of large-scale atmospheric circulation patterns conducive to severe spring and winter wind events over beijing in china based on a machine learning categorizing method |
| title_full | Characteristics of large-scale atmospheric circulation patterns conducive to severe spring and winter wind events over beijing in china based on a machine learning categorizing method |
| title_fullStr | Characteristics of large-scale atmospheric circulation patterns conducive to severe spring and winter wind events over beijing in china based on a machine learning categorizing method |
| title_full_unstemmed | Characteristics of large-scale atmospheric circulation patterns conducive to severe spring and winter wind events over beijing in china based on a machine learning categorizing method |
| title_short | Characteristics of large-scale atmospheric circulation patterns conducive to severe spring and winter wind events over beijing in china based on a machine learning categorizing method |
| title_sort | characteristics of large scale atmospheric circulation patterns conducive to severe spring and winter wind events over beijing in china based on a machine learning categorizing method |
| topic | SOM method large-scale circulation synoptic weather system global warming severe wind event in spring and winter seasons |
| url | https://www.frontiersin.org/articles/10.3389/feart.2022.998108/full |
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