Spatiotemporal distribution of GNSS-derived PWV in Australia from 2010 to 2019
The weather in Australia is significantly influenced by water vapor evaporated from warm ocean surfaces, which is closely associated with various extreme weather events in the region, such as floods, droughts, and bushfires. This study utilizes Precipitable Water Vapor (PWV) data from 15 Global Navi...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2025-07-01
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| Series: | Geodesy and Geodynamics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1674984725000060 |
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| author | Pan Zhao Fuyang Ke Haopeng Wu Min Wei |
| author_facet | Pan Zhao Fuyang Ke Haopeng Wu Min Wei |
| author_sort | Pan Zhao |
| collection | DOAJ |
| description | The weather in Australia is significantly influenced by water vapor evaporated from warm ocean surfaces, which is closely associated with various extreme weather events in the region, such as floods, droughts, and bushfires. This study utilizes Precipitable Water Vapor (PWV) data from 15 Global Navigation Satellite System (GNSS) stations spanning 2010 to 2019 to investigate the spatiotemporal distribution of atmospheric water vapor across Australia, aiming to improve the accuracy of forecasting hazardous weather events. The results indicate distinct regional features in the spatial distribution of PWV. PWV gradually decreases from coastal areas toward inland regions and increases from south to north. Temporally, the overall trend of PWV remains consistent. From an annual trend perspective, most areas exhibit a decline in PWV content, with the exception of the southwestern coastal region, which shows an increasing trend. Furthermore, the study explores the correlations between PWV content and elevation, latitude, and longitude. Among these, latitude demonstrates the strongest correlation with PWV, with a correlation coefficient as high as 0.88, highlighting the significant impact of latitude on water vapor distribution. |
| format | Article |
| id | doaj-art-8dca4767609b45619af86bac2bbb9660 |
| institution | Kabale University |
| issn | 1674-9847 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Geodesy and Geodynamics |
| spelling | doaj-art-8dca4767609b45619af86bac2bbb96602025-08-20T03:24:59ZengKeAi Communications Co., Ltd.Geodesy and Geodynamics1674-98472025-07-0116445446410.1016/j.geog.2024.12.006Spatiotemporal distribution of GNSS-derived PWV in Australia from 2010 to 2019Pan Zhao0Fuyang Ke1Haopeng Wu2Min Wei3The First Geological Brigade of Jiangsu Geological Bureau, Nanjing 210000, China; School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaThe First Geological Brigade of Jiangsu Geological Bureau, Nanjing 210000, China; School of Software, Nanjing University of Information Science & Technology, Nanjing 210044, China; Corresponding author. The First Geological Brigade of Jiangsu Geological Bureau, Nanjing, 210000, China.School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China; Department of Atmospheric Science, Yonsei University, Seoul 03722, South KoreaSchool of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaThe weather in Australia is significantly influenced by water vapor evaporated from warm ocean surfaces, which is closely associated with various extreme weather events in the region, such as floods, droughts, and bushfires. This study utilizes Precipitable Water Vapor (PWV) data from 15 Global Navigation Satellite System (GNSS) stations spanning 2010 to 2019 to investigate the spatiotemporal distribution of atmospheric water vapor across Australia, aiming to improve the accuracy of forecasting hazardous weather events. The results indicate distinct regional features in the spatial distribution of PWV. PWV gradually decreases from coastal areas toward inland regions and increases from south to north. Temporally, the overall trend of PWV remains consistent. From an annual trend perspective, most areas exhibit a decline in PWV content, with the exception of the southwestern coastal region, which shows an increasing trend. Furthermore, the study explores the correlations between PWV content and elevation, latitude, and longitude. Among these, latitude demonstrates the strongest correlation with PWV, with a correlation coefficient as high as 0.88, highlighting the significant impact of latitude on water vapor distribution.http://www.sciencedirect.com/science/article/pii/S1674984725000060AustraliaGNSS-derived PWVSpatial distribution characteristicsMulti-scale analysisClimate variability |
| spellingShingle | Pan Zhao Fuyang Ke Haopeng Wu Min Wei Spatiotemporal distribution of GNSS-derived PWV in Australia from 2010 to 2019 Geodesy and Geodynamics Australia GNSS-derived PWV Spatial distribution characteristics Multi-scale analysis Climate variability |
| title | Spatiotemporal distribution of GNSS-derived PWV in Australia from 2010 to 2019 |
| title_full | Spatiotemporal distribution of GNSS-derived PWV in Australia from 2010 to 2019 |
| title_fullStr | Spatiotemporal distribution of GNSS-derived PWV in Australia from 2010 to 2019 |
| title_full_unstemmed | Spatiotemporal distribution of GNSS-derived PWV in Australia from 2010 to 2019 |
| title_short | Spatiotemporal distribution of GNSS-derived PWV in Australia from 2010 to 2019 |
| title_sort | spatiotemporal distribution of gnss derived pwv in australia from 2010 to 2019 |
| topic | Australia GNSS-derived PWV Spatial distribution characteristics Multi-scale analysis Climate variability |
| url | http://www.sciencedirect.com/science/article/pii/S1674984725000060 |
| work_keys_str_mv | AT panzhao spatiotemporaldistributionofgnssderivedpwvinaustraliafrom2010to2019 AT fuyangke spatiotemporaldistributionofgnssderivedpwvinaustraliafrom2010to2019 AT haopengwu spatiotemporaldistributionofgnssderivedpwvinaustraliafrom2010to2019 AT minwei spatiotemporaldistributionofgnssderivedpwvinaustraliafrom2010to2019 |