The Spatiotemporal Clustering of Short‐Duration Rainstorms in Shanghai City Using a Sub‐Hourly Gauge Network
Abstract Impacted by both the large‐scale climate change and the local hydrometeorological atmosphere, the spatiotemporal structure and properties of short‐duration extreme rainfall events in urban areas remain a complex issue. This study explores the spatiotemporal pattern variability of short‐dura...
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| Format: | Article |
| Language: | English |
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American Geophysical Union (AGU)
2024-03-01
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| Series: | Earth and Space Science |
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| Online Access: | https://doi.org/10.1029/2023EA003442 |
| _version_ | 1797218173848649728 |
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| author | Nuo Lei Lisha Gao Shuguang Liu Zhengzheng Zhou |
| author_facet | Nuo Lei Lisha Gao Shuguang Liu Zhengzheng Zhou |
| author_sort | Nuo Lei |
| collection | DOAJ |
| description | Abstract Impacted by both the large‐scale climate change and the local hydrometeorological atmosphere, the spatiotemporal structure and properties of short‐duration extreme rainfall events in urban areas remain a complex issue. This study explores the spatiotemporal pattern variability of short‐duration rainstorm events using an exceptional sub‐hourly gauge network in Shanghai, China. A catalog of 207 “independent” rainstorms is extracted. The hierarchical clustering method is used to examine the spatial and temporal features including rainfall duration, intensity, and coverage for each district with different degrees of urbanization in the 2014–2018 period. The results point to a pronounced spatial heterogeneity with heavier rainfall magnitude in the north. In the urban core area, intensive short‐duration rainstorms hit more frequently than in other districts. Rainstorms can be divided into three types from the spatiotemporal process: Type delayed‐slow, Type advanced‐fast, and Type advanced‐slow. The delayed‐peak with a higher slope occurs more in the west and the advanced‐peak more along the coastal line. The other type of advanced‐peak storm with a reverse trend of intensity and coverage concentrates in June–August of the year and the 16:00–20:00 of the day. While 65.6% of the delayed‐peak storms only occur in one district, more than half of the advanced‐peak appear without other types at the same time. These findings show the importance of observation‐based analysis in understanding the spatiotemporal pattern of short‐duration storms and provide a reference for storm design of sub‐regions in urban areas. |
| first_indexed | 2024-04-24T12:13:33Z |
| format | Article |
| id | doaj.art-5ee449296acb4d8b8ba85bbc5ee4da67 |
| institution | Directory Open Access Journal |
| issn | 2333-5084 |
| language | English |
| last_indexed | 2024-04-24T12:13:33Z |
| publishDate | 2024-03-01 |
| publisher | American Geophysical Union (AGU) |
| record_format | Article |
| series | Earth and Space Science |
| spelling | doaj.art-5ee449296acb4d8b8ba85bbc5ee4da672024-04-08T08:47:01ZengAmerican Geophysical Union (AGU)Earth and Space Science2333-50842024-03-01113n/an/a10.1029/2023EA003442The Spatiotemporal Clustering of Short‐Duration Rainstorms in Shanghai City Using a Sub‐Hourly Gauge NetworkNuo Lei0Lisha Gao1Shuguang Liu2Zhengzheng Zhou3Department of Hydraulic Engineering Tongji University Shanghai ChinaShanghai Water Planning and Design Research Institute Shanghai Ocean Planning and Design Research Institute Shanghai ChinaDepartment of Hydraulic Engineering Tongji University Shanghai ChinaDepartment of Hydraulic Engineering Tongji University Shanghai ChinaAbstract Impacted by both the large‐scale climate change and the local hydrometeorological atmosphere, the spatiotemporal structure and properties of short‐duration extreme rainfall events in urban areas remain a complex issue. This study explores the spatiotemporal pattern variability of short‐duration rainstorm events using an exceptional sub‐hourly gauge network in Shanghai, China. A catalog of 207 “independent” rainstorms is extracted. The hierarchical clustering method is used to examine the spatial and temporal features including rainfall duration, intensity, and coverage for each district with different degrees of urbanization in the 2014–2018 period. The results point to a pronounced spatial heterogeneity with heavier rainfall magnitude in the north. In the urban core area, intensive short‐duration rainstorms hit more frequently than in other districts. Rainstorms can be divided into three types from the spatiotemporal process: Type delayed‐slow, Type advanced‐fast, and Type advanced‐slow. The delayed‐peak with a higher slope occurs more in the west and the advanced‐peak more along the coastal line. The other type of advanced‐peak storm with a reverse trend of intensity and coverage concentrates in June–August of the year and the 16:00–20:00 of the day. While 65.6% of the delayed‐peak storms only occur in one district, more than half of the advanced‐peak appear without other types at the same time. These findings show the importance of observation‐based analysis in understanding the spatiotemporal pattern of short‐duration storms and provide a reference for storm design of sub‐regions in urban areas.https://doi.org/10.1029/2023EA003442short‐duration rainstormspatial‐temporal characteristichierarchical clusteringurban areasspatiotemporal process |
| spellingShingle | Nuo Lei Lisha Gao Shuguang Liu Zhengzheng Zhou The Spatiotemporal Clustering of Short‐Duration Rainstorms in Shanghai City Using a Sub‐Hourly Gauge Network Earth and Space Science short‐duration rainstorm spatial‐temporal characteristic hierarchical clustering urban areas spatiotemporal process |
| title | The Spatiotemporal Clustering of Short‐Duration Rainstorms in Shanghai City Using a Sub‐Hourly Gauge Network |
| title_full | The Spatiotemporal Clustering of Short‐Duration Rainstorms in Shanghai City Using a Sub‐Hourly Gauge Network |
| title_fullStr | The Spatiotemporal Clustering of Short‐Duration Rainstorms in Shanghai City Using a Sub‐Hourly Gauge Network |
| title_full_unstemmed | The Spatiotemporal Clustering of Short‐Duration Rainstorms in Shanghai City Using a Sub‐Hourly Gauge Network |
| title_short | The Spatiotemporal Clustering of Short‐Duration Rainstorms in Shanghai City Using a Sub‐Hourly Gauge Network |
| title_sort | spatiotemporal clustering of short duration rainstorms in shanghai city using a sub hourly gauge network |
| topic | short‐duration rainstorm spatial‐temporal characteristic hierarchical clustering urban areas spatiotemporal process |
| url | https://doi.org/10.1029/2023EA003442 |
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