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GNSS Meteorology for Disastrous Rainfalls in 2017-2019 Summer in SW Japan: A New Approach Utilizing Atmospheric Delay Gradients
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Title: | GNSS Meteorology for Disastrous Rainfalls in 2017-2019 Summer in SW Japan: A New Approach Utilizing Atmospheric Delay Gradients |
Authors: | Arief, Syachrul Browse this author | Heki, Kosuke Browse this author →KAKEN DB |
Keywords: | heavy rain | GNSS | Japan | tropospheric gradient | water vapor convergence | zenith wet delay |
Issue Date: | 23-Jun-2020 |
Publisher: | Frontiers Media |
Journal Title: | Frontiers in earth science |
Volume: | 8 |
Start Page: | 182 |
Publisher DOI: | 10.3389/feart.2020.00182 |
Abstract: | We studied disastrous heavy rainfall episodes in 2017-2019 summer in SW Japan, especially in the Kyushu region using tropospheric delay data from the Japanese dense global navigation satellite system (GNSS) network GEONET (GNSS Earth Observation Network). This region often suffers from extremely heavy rains associated with stationary fronts during summer. In this study, we first analyze behaviors of water vapor on July 6, 2018, using tropospheric parameters obtained from the database at the University of Nevada, Reno. The data set includes tropospheric delay gradient vectors (G), as well as zenith tropospheric delays (ZTD), estimated every 5 min. At first, we interpolatedGto obtain those at grid points and calculated their convergence, similar to the quantity proposed byShoji (2013)as water vapor concentration (WVC) index. We obtained zenith wet delay (ZWD) from ZTD by removing zenith hydrostatic delay. The raw ZWD values do not really reflect the wetness of the atmosphere above the GNSS station because they largely depend on the station altitudes. To study the dynamics of water vapor before heavy rains, we estimated ZWD converted to the values at sea level. In the inversion scheme, we usedGat all GEONET stations and ZWD data at low-altitude (<100 m) GEONET stations as the input. Then we assumed that spatial change of ZWD is proportional toG(e.g.,G(x)=H partial differential ZWD/ partial differential x, whereHis the water vapor scale height) and estimated sea-level ZWD at grid points all over Japan. At last, we tried to justify our working hypothesis that heavy rain occurs when both WVC and sea-level ZWD are high by analyzing hourly water vapor distributions in all the days in July 2017, July 2018, and August 2019. We found that both two values showed maxima in the studied period when the three heavy rainfall (>50 mm/h) episodes occurred, that is, July 5, 2017, July 6, 2018, and August 27, 2019. Next, we performed high time resolution analysis (every 5 min) on the days of heavy rain. The results suggest that both WVC and sea-level ZWD go up prior to the onset of the rain, and ZWD decreases rapidly once the heavy rain started. It is a future issue, however, how far these two quantities contribute to forecast heavy rains. |
Rights: | https://creativecommons.org/licenses/by/4.0/ |
Type: | article |
URI: | http://hdl.handle.net/2115/79085 |
Appears in Collections: | 理学院・理学研究院 (Graduate School of Science / Faculty of Science) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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