- 著者
- Kyohei Yamada Masatoshi Kuribayashi
- 出版者
- Meteorological Society of Japan
- 雑誌
- SOLA (ISSN:13496476)
- 巻号頁・発行日
- vol.17A, no.Special_Edition, pp.45-50, 2021 (Released:2021-08-12)
- 参考文献数
- 24
- 被引用文献数
- 1
In October of 2019, Typhoon Hagibis brought abundant rainfall to eastern Japan that caused flooding of the Chikuma River in the northern region of Nagano prefecture. This study simulated the effects of changes in the elevation of the model terrain every 100 or 300 m with a regional meteorological model to understand the cause of the heavy precipitation that accompanied the typhoon in Nagano prefecture and the influence of the heights of mountains on the amount of rainfall. The model reproduced the typhoon track and spatiotemporal distribution of heavy precipitation. Mountains in the northern region of Nagano Prefecture contributed to the heavy precipitation, which increased at an approximately constant rate of 4.4 mm per 100 m increase of elevation. However, the rate of increase was especially large at elevations of 900-1200 m. The correlation of precipitation with topographic height was not as strong in the south as in the north, but the rate of variation was also anomalously high at elevations of 900-1200 m. These elevations roughly corresponded to the level of free convection or to elevations between the level of free convection and the lifted condensation level around the typhoon track.
- 著者
- Kyohei Yamada Masatoshi Kuribayashi
- 出版者
- Meteorological Society of Japan
- 雑誌
- SOLA (ISSN:13496476)
- 巻号頁・発行日
- pp.17A-008, (Released:2021-07-15)
- 被引用文献数
- 1
In October of 2019, Typhoon Hagibis brought abundant rainfall to eastern Japan that caused flooding of the Chikuma River in the northern region of Nagano prefecture. This study simulated the effects of changes in the elevation of the model terrain every 100 or 300 m with a regional meteorological model to understand the cause of the heavy precipitation that accompanied the typhoon in Nagano prefecture and the influence of the heights of mountains on the amount of rainfall. The model reproduced the typhoon track and spatiotemporal distribution of heavy precipitation. Mountains in the northern region of Nagano Prefecture contributed to the heavy precipitation, which increased at an approximately constant rate of 4.4 mm per 100 m increase of elevation. However, the rate of increase was especially large at elevations of 900-1200 m. The correlation of precipitation with topographic height was not as strong in the south as in the north, but the rate of variation was also anomalously high at elevations of 900-1200 m. These elevations roughly corresponded to the level of free convection or to elevations between the level of free convection and the lifted condensation level around the typhoon track.
- 著者
- Masatoshi Kuribayashi Nam Jin Noh Taku M. Saitoh Ichiro Tamagawa Yasutaka Wakazuki Hiroyuki Muraoka
- 出版者
- (公社)日本気象学会
- 雑誌
- SOLA (ISSN:13496476)
- 巻号頁・発行日
- vol.9, pp.148-152, 2013 (Released:2013-10-11)
- 参考文献数
- 26
- 被引用文献数
- 3 8
We estimated the snow water equivalent (SWE) of snowpack in central Japan from September 2006 to August 2008 by using a 3.3 km-mesh regional climate model with two land-surface models: Noah land-surface model (Noah LSM), and Noah land-surface model with multiparameterization options (Noah MP). The model validation for temporal variations of SWE at the Tohkamachi station and the comparison of modeled maximum SWE with estimated that from observed maximum snow depth at ten sites showed that Noah MP could simulate spatiotemporal variations of SWE better than Noah LSM which underestimated SWE. Simulated SWE in central Japan peaked in March, but the difference of SWE between the two land-surface models was greatest in April. SWE determined using Noah LSM (Noah MP) in analysis domain reached 18.1% (28.5%) of the total storage capacity of high dams in Japan in March 2007, whereas it reached 32.4% (44.1%) in March 2008. The difference of SWE between the two land-surface models was particularly high under warm conditions, that is, during the snowmelt season, and during a warmer than normal winter. Our results indicate that the choice of land-surface model for estimates of SWE is important under warm climatic conditions.