PERPUSTAKAAN BIG

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Meteorological application of a dense GNSS network utilizing atmospheric delay gradient and crustal subsidence: the 2018 disastrous rain episode in SW Japan

Syachrul Arief - Nama Orang;

Heavy rain late June to early July 2018 disastours flood in Southwest (SW) Japan, especially in Kyushu. By using a dense array of Global Navigation Satellite System (GNSS) receivers in Japan GEONET, I study this two different space geodetic approaches, i.e, measurements of atmospheric water vapor and crustal deformation due to surface water load.
The first approach is the recovery of precipitable water vapor (PWV) using the zenith wet delays (ZWD) because atmospheric water vapor concentrates in relatively low altitutes, 2-D distribution of ZWDs often repsent that of elevation of the observing stations rather than the relative humidity of the air colomn above the stations. To overcome the difficulty, I reconstructed ZWDs converted to sea-level values by spatially integrating the tropospheric delay gradient (azimuthal asymmetry of water vapor convergence (WVC) index proposed by Shoji (2013). I found that extreme rainfall occourse in the region and time, where both the sea-level ZWD and the WVC index are high. I Confirmed this was the case also similar disastrous heavy rain episodes in SW Japan in 2017 Juky and 2019 August.
Next, I Studies vertical crustal movements associated with surface water loads broght by heavy rainfall, using the official F3 solution of the GEONET station coordinates. Rainwater would act as the surface load and depress the ground to a detectable level. I removed common mode errors by adjusting-100 reference stations to the median position over a 1-month period using the flooded areas to the sea. Then, I estimated the distribution of surface water load over the entire SW Japan using the GNSS station subsidence as the input. The estimated distribution of surface water resembled to the rainfall distribution from the AMEDAS rain gauge data from Japan Meteorological Agency (JMA).


Ketersediaan
B202001117047DS 526.1 SYA mPerpustakaan BIG (500)Tersedia
Informasi Detail
Judul Seri
-
No. Panggil
DS 526.1 SYA m
Penerbit
Japan : Hokaido University., 2020
Deskripsi Fisik
86 hlm. : illus. ; 29 cm.
Bahasa
Inggris
ISBN/ISSN
-
Klasifikasi
526.1
Tipe Isi
text
Tipe Media
other
Tipe Pembawa
unspecified
Edisi
-
Subjek
Geodesi
Info Detail Spesifik
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Pernyataan Tanggungjawab
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Perpustakaan Badan Informasi Geospasial (BIG) adalah sebuah perpustakaan yang berada di bawah Badan Informasi Geospasial Indonesia. Perpustakaan ini memiliki koleksi yang berkaitan dengan informasi geospasial, termasuk peta, data geospasial, dan literatur terkait. Selengkapnya

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