Japan Geoscience Union Meeting 2021

Presentation information

[J] Poster

A (Atmospheric and Hydrospheric Sciences ) » A-AS Atmospheric Sciences, Meteorology & Atmospheric Environment

[A-AS07] Weather, Climate, and Environmental Science Studies using High-Performance Computing

Fri. Jun 4, 2021 5:15 PM - 6:30 PM Ch.07

convener:Hisashi Yashiro(National Institute for Environmental Studies), Takuya Kawabata(Meteorological Research Institute), Tomoki Miyakawa(Atmosphere and Ocean Research Institute, The University of Tokyo), Koji Terasaki(RIKEN Center for Computational Science)

5:15 PM - 6:30 PM

[AAS07-P09] Application of the microphysics process-tracking scheme to simulations of the intense snowfall event in early 2018, Japan

*Akihiro Hashimoto1, Katsuya Yamashita2, Masaaki Ishizaka2, Hiroki Motoyoshi2, Sento Nakai2, Satoru Yamaguchi2 (1.Meteorological Research Institute, 2.National Research Institute for Earth Science and Disaster Resilience)

In January and February 2018, cold outbreak events brought intense snowfalls to the San-in, Hokuriku, and Tohoku districts of Japan, and caused considerable damage to local societies. The authors performed numerical weather simulations of these snowfalls using the new method of diagnosing characteristics of ice particles proposed by Hashimoto et al. (2020), which tracks the mass compositions of different classes of ice particles using their microphysical process of origin, such as water vapor deposition and riming. The mass composition from depositional growth is further divided into six components by the temperature and humidity ranges corresponding to the typical growth habits of ice crystals.
As a result, the precipitation from longitudinal- or transverse-mode cloud bands was most composed of graupel particles, while rimed snow particles were the major contributor to the JPCZ-related precipitation. The difference of hydrometeor type between the cloud bands and JPCZ-related cloud system was qualitatively supported by observation. On the other hand, in terms of reproducibility of the size and fall velocity at the centre of mass flux distribution (CMF, Ishizaka et al., 2016), there was room for improvement of the model.

Acknowledgements
This work was supported in part by the Japan Society for the Promotion of Science, KAKENHI Grant Numbers JP16K05557, and JP19K04978.

References
Hashimoto, A., H. Motoyoshi, N. Orikasa, and R. Misumi, 2020: Process-tracking scheme based on bulk microphysics to diagnose the features of snow particles. SOLA, 16, 51-56, https://doi.org/10.2151/sola.2020-009.

Ishizaka, M., Motoyoshi, H., Yamaguchi, S., Nakai, S., Shiina, T., and Muramoto, K.-I., 2016: Relationships between snowfall density and solid hydrometeors, based on measured size and fall speed, for snowpack modeling applications, The Cryosphere, 10, 2831–2845, https://doi.org/10.5194/tc-10-2831-2016.