Review:
Overview: Results of Snow and Ice Disaster Mitigation Conducted by the National Research Institute for Earth Science and Disaster Resilience
Satoru Yamaguchi*, , Masaki Nemoto**, Takahiro Tanabe**, Sojiro Sunako*, Satoru Adachi**, Kengo Sato**, Katsuya Yamashita*, Hiroyuki Hirashima* , Yoichi Ito*, Hiroki Motoyoshi*, Hayato Arakawa**, Kazuki Namakura*, Sento Nakai*, Isao Kamiishi*, Kazuma Togashi**, and Kenji Kosugi**
*Snow and Ice Research Center, National Research Institute for Earth Science and Disaster Resilience
187-16 Maeyama, Suyoshi, Nagaoka, Niigata 940-0821, Japan
Corresponding author
**Shinjo Cryospheric Environment Laboratory, Snow and Ice Research Center, National Research Institute for Earth Science and Disaster Resilience
Shinjo, Japan
More than half of Japan’s land area experiences significant snowfall during winter, and the damage caused by various snow and ice disasters remains a dire issue, which also leads to decreased living standards. Simultaneously, the nature of snow and ice disasters has been transformed due to climate change and the increasing occurrence of extreme weather conditions. The National Research Institute for Earth Science and Disaster Resilience (NIED) has been continuously conducting research to address these problems in relation to snow and ice disasters. This study presents the results of the project “Research on Combining Risk Monitoring and Forecasting Technologies for Mitigation of Increasingly Diverse Snow Disaster” conducted by the NIED over a seven-year period from April 2016 to March 2023. This project developed technology for conducting accurate observations of snowfall and snow cover conditions over wide areas as well as technology for areal prediction of snow and ice disasters through simulations. Based on collaboration with stakeholders, such as local governments, our study investigated how to optimize the use of our information products for snow and ice disaster mitigation. Through these insights, the NIED provides information for prompt and appropriate responses to snow and ice disasters, thus supporting safe and comfortable living in both snowy and non-snowy areas.
- [1] S. Nakai et al., “Study on advanced snow information and its application to disaster mitigation: An overview,” Bulletin of Glaciological Research, Vol.37S, pp. 3-19, 2019. https://doi.org/10.5331/bgr.18SW01
- [2] I. Kamiishi and K. Nakamura, “Snow disaster caused by a cyclonic heavy snowfall in February, 2014, and countermeasures taken by the NIED and its future direction for disaster prevention,” Natural Disaster Research Report of the National Research Institute for Earth Science and Disaster Resilience, Vol.49, pp. 1-10, 2016 (in Japanese with English abstract).
- [3] S. Nakai et al., “A Snow Disaster Forecasting System (SDFS) constructed from field observations and laboratory experiments,” Cold Regions Science and Technology, Vol.70, pp. 53-61, 2012. https://doi.org/10.1016/j.coldregions.2011.09.002
- [4] K. Yamashita et al., “Quantitative snowfall distribution acquisition system with high spatiotemporal resolution using existing snowfall sensors,” SOLA, Vol.16, pp. 271-276, 2020. https://doi.org/10.2151/sola.2020-045
- [5] S. Nakai, K. Iwanami, R. Misumi, S.-G. Park, and T. Kobayashi, “A classification of snow clouds by Doppler radar observations at Nagaoka, Japan,” SOLA, Vol.1, pp. 161-164, 2005. https://doi.org/10.2151/sola.2005-042
- [6] A. Masuda et al., “Improving of winter quantitative precipitation estimation using XRAIN,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.74, No.4, pp. I_85-I_90, 2018 (in Japanese). https://doi.org/10.2208/jscejhe.74.I_85
- [7] N. Mizuta, H. Takenaka, T. Sano, and K. Fukami, “Approach to accuracy improvement of rainfall intensity observed by multi-parameter radars in XRAIN of MLIT,” Preprints of the River Information Symp. in the 3rd Fiscal Year of Reiwa, 2021 (in Japanese). https://www.river.or.jp/01kenshuu/sympo/r03/img/report_07.pdf [Accessed March 27, 2024]
- [8] H. Yamaji, S. Tsuchiya, and M. Kawasaki, “High-precision wide-area rainfall observation by C-band polarimetric radars and XRAIN,” Civil Engineering J., Vol.58, No.7, pp. 26-29, 2016 (in Japanese). https://www.pwrc.or.jp/thesis_shouroku/thesis_pdf/1607-P026-029_yamaji.pdf [Accessed March 27, 2024]
- [9] I. Wakayama, T. Imai, T. Kitamura, and K. Kobayashi, “About estimated weather distribution,” Weather Service Bulletin, Vol.87, pp. 1-18, 2020 (in Japanese).
- [10] H. Hirashima, T. Iyobe, K. Kawashima, and H. Sano, “Development of a snow load alert system, ‘YukioroSignal’ for aiding roof snow removal decisions in snowy areas in Japan,” J. Disaster Res., Vol.15, No.6, pp. 688-697, 2020. https://doi.org/10.20965/jdr.2020.p0688
- [11] T. Iyobe and K. Kawashima, “Development of quasi-real-time monitoring system for regional snow cover by utilizing multiple snow data,” J. of Snow Engineering of Japan, Vol.36, No.1, pp. 1-13, 2020 (in Japanese with English abstract). https://doi.org/10.32120/jsej.36.1_1
- [12] H. Hirashima, “Numerical snowpack model simulation schemes for avalanche prediction in Japan,” Bulletin of Glaciological Research, Vol.37S, pp. 31-41, 2019. https://doi.org/10.5331/bgr.18SW02
- [13] K. Nakamura, S. Sunako, I. Kamiishi, A. Miyazima, and J. Chujo, “Development of smartphone road surface condition interpretation system by using artificial intelligence model,” Proc. of Cold Region Technology Conf., Vol.38, pp. 103-108, 2022 (in Japanese).
- [14] K. Saito et al., “The operational JMA nonhydrostatic mesoscale model,” Monthly Weather Review, Vol.134, No.4, pp. 1266-1298, 2006. https://doi.org/10.1175/MWR3120.1
- [15] T. Asai, “Meso-scale features of heavy snowfalls in Japan Sea coastal regions of Japan,” Tenki, Vol.35, No.3, pp. 156-161, 1988 (in Japanese).
- [16] I. Kamiishi, K. Namakura, S. Adachi, and K. Yamashita, “Avalanche disaster caused by a cyclonic heavy snowfall on February, 2014,” Natural Disaster Research Report of the National Research Institute for Earth Science and Disaster Resilience, Vol.49, pp. 31-37, 2016 (in Japanese with English abstract).
- [17] K. Nakamura, “Implementation and demonstration of a system for the forecasting of surface avalanche potential caused by snowfall from a cyclone,” J. Disaster Res., Vol.14, No.9, pp. 1201-1226, 2019. https://doi.org/10.20965/jdr.2019.p1201
- [18] K. Nakamura, K. Nishida, and Y. Saito, “Improvement of a system for the forecasting of surface avalanche potential caused by snowfall from a cyclone,” Proc. of Cold Region Technology Conf., Vol.37, pp. 57-62, 2021 (in Japanese).
- [19] K. Nakamura, “Improvement of a potential estimation algorithm for surface avalanches caused by snowfall during a cyclone,” J. Disaster Res., Vol.17, No.6, pp. 956-975, 2022. https://doi.org/10.20965/jdr.2022.p0956
- [20] T. Sato et al., “Wide-area forecasting of poor visibility due to blowing snow,” Proc. of Cold Region Technology Conf., Vol.20, pp. 332-337, 2004 (in Japanese).
- [21] T. Sato, M. Nemoto, I. Kamiishi, H. Motoyoshi, and S. Nakai, “Prediction of poor visibility due to blowing snow and its verification – Application to measures against blowing snow disasters by Niigata City during 2010/2011 winter –,” Natural Disaster Research Report of the National Research Institute for Earth Science and Disaster Resilience, Vol.47, pp. 103-112, 2012 (in Japanese with English abstract).
- [22] O. Abe and K. Kosugi, “Twenty-year operation of the cryospheric environment simulator,” Bulletin of Glaciological Research, Vol.37S, pp. 53-65, 2019. https://doi.org/10.5331/bgr.16SR01
- [23] M. Nemoto, I. Kamiishi, and K. Nakamura, “The application of a blowing snow prediction system in Nakashibetsu, Hokkaido, in the winter of 2014/15,” Natural Disaster Research Report of the National Research Institute for Earth Science and Disaster Resilience, Vol.49, pp. 119-122, 2016 (in Japanese with Englih abstract).
- [24] S. Yamaguchi et al., “Co-creation with local governments and ski resorts to generate scientific information that contributing to ski resort avalanche safety management,” Bulletin of Glaciological Research, Vol.42, pp. 9-17, 2024. https://doi.org/10.5331/bgr.23R02
- [25] S. Yamaguchi, S. Matoba, M. Niwano, T. Aoki, and K. Kosugi, “Database of long-term meteorological and snow-pit observations in Japan,” Proc. Int. Snow Science Workshop, pp. 582-585, 2018.
- [26] S. Yamaguchi, O. Abe, S. Nakai, and A. Sato, “Recent fluctuations of meteorological and snow conditions in Japanese mountains,” Annals of Glaciology. Vol.52, No.58, pp. 209-215, 2011. https://doi.org/10.3189/172756411797252266
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