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[AAS10-04] Study on the density of snowfall particles during past heavy snowfall events around Sapporo, Hokkaido
Keywords:snowfall, precipitation
Study on the density of snowfall particles during past heavy snowfall events around Sapporo, Hokkaido
This study examined the densities of snowfall particles of heavy snowfall events around Sapporo, Hokkaido by analyzing the data of the ground base measurement for the precipitation amount and the snow depth based on the method of Tanji et al. (2022). The analyses elucidated that 57 heavy snowfall events observed over the past 17 years. The observed snowfall density during the heavy snowfall event on 11-12 January 2022, which was record-breaking heavy snowfall in Hokkaido, was highest among the 57 events. The analyses also indicated that the snowfall particles with high density, i.e., heavy snow particles, were mostly originated from the snow clouds accompanying with the low pressure systems. To understand the reason that the snowfall particles were heavy, we conducted numerical experiments by using a model that explicitly predicts the deposition and riming growth rate (Hashimoto et al., 2020). The results of the experiments indicated that the snowfall and the rain were both simulated around the surface and the surface temperature was around 0 oC, when the heavy snowfall particles were observed. The result suggests that the partially melted snowfall particles would be one the reasons of the heavy snow.
References
1. Kazuhiro Tanji , Toshihiro Ozeki, Naoki Matsuoka , Yasuhiro Kaneda , Naotoshi Kanemura , Asami Komatsu, 2022: Seppyo, 41, 5-8. (in Japanese)
2. Kojima K, Viscous Compression of Natural Snow-Laper Ⅰ., Low temperature science. Series A, Physical sciences, 14, 77-93. (in Japanese)
3. Kojima K, Viscous Compression of Natural Snow Laper. Ⅱ., Low temperature science. Series A, Physical sciences, 15, 117-135. (in Japanese)
4. Kojima K, Viscous Compression of Natural Snow Layers. Ⅲ., Low temperature science. Series A, Physical sciences, 16, 167-196. (in Japanese)
5. Nishizawa, S., Yashiro, H., Sato, Y., Miyamoto, Y. & Tomita, H. Influence of grid aspect ratio on planetary boundary layer turbulence in large-eddy simulations. Geosci. Model Dev. 8, 3393–3419 (2015).
6. Sato, Y. S. Nishizawa, H. Yashiro, Y. Miyamoto, Y. Kajikawa, & H.Tomita, Impacts of cloud microphysics on trade wind cumulus: which cloud microphysicsprocesses contribute to the diversity in a large eddy simulation? Prog. EarthPlanet. Sci. 2, (2015).
7. Hashimoto A.,Motoyoshi H.,Orikasa N.,and Misumi R.,2020:Process-Tracking Scheme Based on Bulk Microphysics to Diagnose the Features of Snow Particles,SOLA,16,51–56.
This study examined the densities of snowfall particles of heavy snowfall events around Sapporo, Hokkaido by analyzing the data of the ground base measurement for the precipitation amount and the snow depth based on the method of Tanji et al. (2022). The analyses elucidated that 57 heavy snowfall events observed over the past 17 years. The observed snowfall density during the heavy snowfall event on 11-12 January 2022, which was record-breaking heavy snowfall in Hokkaido, was highest among the 57 events. The analyses also indicated that the snowfall particles with high density, i.e., heavy snow particles, were mostly originated from the snow clouds accompanying with the low pressure systems. To understand the reason that the snowfall particles were heavy, we conducted numerical experiments by using a model that explicitly predicts the deposition and riming growth rate (Hashimoto et al., 2020). The results of the experiments indicated that the snowfall and the rain were both simulated around the surface and the surface temperature was around 0 oC, when the heavy snowfall particles were observed. The result suggests that the partially melted snowfall particles would be one the reasons of the heavy snow.
References
1. Kazuhiro Tanji , Toshihiro Ozeki, Naoki Matsuoka , Yasuhiro Kaneda , Naotoshi Kanemura , Asami Komatsu, 2022: Seppyo, 41, 5-8. (in Japanese)
2. Kojima K, Viscous Compression of Natural Snow-Laper Ⅰ., Low temperature science. Series A, Physical sciences, 14, 77-93. (in Japanese)
3. Kojima K, Viscous Compression of Natural Snow Laper. Ⅱ., Low temperature science. Series A, Physical sciences, 15, 117-135. (in Japanese)
4. Kojima K, Viscous Compression of Natural Snow Layers. Ⅲ., Low temperature science. Series A, Physical sciences, 16, 167-196. (in Japanese)
5. Nishizawa, S., Yashiro, H., Sato, Y., Miyamoto, Y. & Tomita, H. Influence of grid aspect ratio on planetary boundary layer turbulence in large-eddy simulations. Geosci. Model Dev. 8, 3393–3419 (2015).
6. Sato, Y. S. Nishizawa, H. Yashiro, Y. Miyamoto, Y. Kajikawa, & H.Tomita, Impacts of cloud microphysics on trade wind cumulus: which cloud microphysicsprocesses contribute to the diversity in a large eddy simulation? Prog. EarthPlanet. Sci. 2, (2015).
7. Hashimoto A.,Motoyoshi H.,Orikasa N.,and Misumi R.,2020:Process-Tracking Scheme Based on Bulk Microphysics to Diagnose the Features of Snow Particles,SOLA,16,51–56.