稠密GNSS可降水量観測ネットワークと非静力学モデルを用いた深い対流に伴う水蒸気変動に関する研究

京都大学0048新制・課程博士博士(理学)甲第19505号理博第4165号新制||理||1598(附属図書館)32541京都大学大学院理学研究科地球惑星科学専攻(主査)教授 津田 敏隆, 教授 石川 裕彦, 教授 余田 成男学位規則第4条第1項該当Doctor of ScienceKyoto UniversityDFA

Numerical Simulation on Retrieval of Meso-γ; Scale Precipitable Water Vapor Distribution with the Quasi-Zenith Satellite System (QZSS)

A simulation study was conducted to investigate the retrieval of meso-γ scale precipitable water vapor (PWV) distribution with the Quasi-Zenith Satellite System (QZSS) using output from a non-hydrostatic model (JMA NHM). The evaluation was performed on PWV values obtained by simulating three different methods: using all GPS satellites above an elevation angle higher than 10° (PWVG) (conventional Global Navigation Satellite System (GNSS) meteorology method), using only the QZSS satellite at the highest elevation (PWVQ), and using only the GPS satellite at the highest elevation (PWVHG).  The three methods were compared by assuming the vertically integrated water vapor amounts of the model as true PWV. As a result, the root mean square errors of PWVG, PWVQ, and PWVHG were 2.78, 0.13, and 0.59 mm, respectively, 5 min before the rainfall. The time series of PWVHG had a large discontinuity (˜ 2 mm) when the GPS satellite with the highest elevation changed, while that of PWVQ was small because the elevation at which the highest QZSS satellites change was much higher. The standard deviation of PWVQ was smaller than those of PWVG and PWVHG, which vary significantly depending on GPS satellite geometry.  When the spatial distributions of PWVG and PWVQ were compared to the meso-γ scale distribution of the reference PWV, PWVG smoothed out the PWV fluctuations, whereas PWVQ captured them well, due to the higher spatial resolution achievable using only high-elevation slant paths. These results suggest that meso-γ scale water vapor fluctuations associated with a thunderstorm can be retrieved using a dense GNSS receiver network and analyzing PWV from a single high-elevation GNSS satellite. In this study, we focus on QZSS, since this constellation would be especially promising in this context, and it would provide nearly continuous PWV observations as its highest satellite changes, contrary to using the highest satellites from multiple GNSS constellations

A High-Resolution, Precipitable Water Vapor Monitoring System Using a Dense Network of GNSS Receivers

This work describes a system aimed at the near realtimemonitoring of precipitable water vapor (PWV) by means of a dense network of Global Navigation Satellite System (GNSS) receivers. These receivers are deployed with a horizontal spacing of 1-2 km around the Uji campus of Kyoto University, Japan. The PWV observed using a standard GPS meteorology technique, i.e., by using all satellites above a low elevation cutoff, is validated against radiosonde and radiometer measurements. The result is a RMS difference of about 2 mm. A more rigorous validation is done by selecting single GPS slant delays as they pass close to the radiosonde or the radiometer measuring directions, and higher accuracy is obtained. This method also makes it possible to preserve short-term fluctuations that are lost in the standard technique due to the averaging of several slant delays. Geostatistical analysis of the PWV observations shows that they are spatially correlated within the area of interest; this confirms that such a dense network can detect inhomogeneous distributions in water vapor. The PWV horizontal resolution is improved by using high-elevation satellites only, with the aim of exploiting at best the future Quasi-Zenith Satellite System (QZSS), which will continuously provide at least one satellite close to the zenith over Japan

Data assimilation experiment of precipitable water vapor observed by a hyper-dense GNSS receiver network using a nested NHM-LETKF system

We studied the assimilation of high-resolution precipitable water vapor (PWV) data derived from a hyper-dense global navigation satellite system network around Uji city, Kyoto, Japan, which had a mean inter-station distance of about 1.7 km. We focused on a heavy rainfall event that occurred on August 13–14, 2012, around Uji city. We employed a local ensemble transform Kalman filter as the data assimilation method. The inhomogeneity of the observed PWV increased on a scale of less than 10 km in advance of the actual rainfall detected by the rain gauge. Zenith wet delay data observed by the Uji network showed that the characteristic length scale of water vapor distribution during the rainfall ranged from 1.9 to 3.5 km. It is suggested that the assimilation of PWV data with high horizontal resolution (a few km) improves the forecast accuracy. We conducted the assimilation experiment of high-resolution PWV data, using both small horizontal localization radii and a conventional horizontal localization radius. We repeated the sensitivity experiment, changing the mean horizontal spacing of the PWV data from 1.7 to 8.0 km. When the horizontal spacing of assimilated PWV data was decreased from 8.0 to 3.5 km, the accuracy of the simulated hourly rainfall amount worsened in the experiment that used the conventional localization radius for the assimilation of PWV. In contrast, the accuracy of hourly rainfall amounts improved when we applied small horizontal localization radii. In the experiment that used the small horizontal localization radii, the accuracy of the hourly rainfall amount was most improved when the horizontal resolution of the assimilated PWV data was 3.5 km. The optimum spatial resolution of PWV data was related to the characteristic length scale of water vapor variability