5:15 PM - 6:45 PM
[AAS08-P01] Numerical simulation of effects of mountain topography on spatial variation of the characteristics of snow particles
★Invited Papers
Keywords:snow crystal, mountain, numerical simulation, snowfall
1. Introduction
Mountain topography affects the heat and water circulation in the atmosphere, and produces cloud and precipitation by forcing an air mass to rise on the slope and generate water condensate with adiabatic cooling, depending on atmospheric conditions. It is desirable that precipitation in mountainous regions is studied from the perspectives of water resources, disasters, tourism, etc. We performed a numerical experiment to investigate the effects of mountain topography on spatial variation of the characteristics of snow particles around the Tateyama mountain range during the heavy snowfall event in December 2022.
2. Numerical experiments
With the same experimental settings as Hashimoto et al. (2020b), we conducted a numerical experiment using the process tracking model (Hashimoto et al., 2020) from December 18th to 19th, 2022. This model can diagnose particle characteristics by tracking the amounts of deposition growth and riming growth of ice particles as prognostic variables. The amounts of deposition growth are tracked separately in several classes with different ranges of temperature and humidity, which roughly represent different growth habits of snow crystals.
3. Results
Simulation results basically showed good agreement with observations, regarding satellite-observed cloud patterns and AWS-observed precipitation amounts. Moist air mass under the winter monsoon outbreak runned into the west coast of the Hokuriku district. Clouds and snowfall developed over the coastal area and extended over the Toyama plain. The air mass further runned inland and raised on the slope of Tateyama mountain range, where the clouds and snowfall developed again. In the coastal area and the upwind slope of the mountain range, riming growth considerably contributed to the snowfall amount. On the other hand, the deposition growth contributed differently to the snowfall amount depending on the ranges of temperature and humidity. The deposition growth in relatively warm temperatures mainly contributed to the snowfall on the upwind slope (western side) of the mountain range, while that in relatively cold temperatures contributed more on the downwind slope (eastern side). Generally, snow particles growing in warmer conditions flow lower in height compared to those growing in colder conditions, as temperature decreases with increasing height. In the simulation, the former snow particles were blocked by the mountain range of 2000 m or more, while the latter snow particles flowed over the mountain range. This result means that snow particles with different growth habits systematically fall on different geographical areas around a mountain range.
Acknowledgements
This work was supported in part by the Japan Society for the Promotion of Science KAKENHI grant number 22K03724, 20H04196, and 23H00729.
References
Hashimoto et al., 2020a: Process-Tracking Scheme Based on Bulk Microphysics to Diagnose the Features of Snow Particles. SOLA, 16, 51−56, doi:10.2151/sola.2020-009.
Hashimoto et al., 2020b: Numerical simulations on the mechanisms of snowfall associated with JPCZ in the 2018 winter. Proceedings of the 2020 autumn meeting of MSJ, PR-23. ( in Japanese)
Mountain topography affects the heat and water circulation in the atmosphere, and produces cloud and precipitation by forcing an air mass to rise on the slope and generate water condensate with adiabatic cooling, depending on atmospheric conditions. It is desirable that precipitation in mountainous regions is studied from the perspectives of water resources, disasters, tourism, etc. We performed a numerical experiment to investigate the effects of mountain topography on spatial variation of the characteristics of snow particles around the Tateyama mountain range during the heavy snowfall event in December 2022.
2. Numerical experiments
With the same experimental settings as Hashimoto et al. (2020b), we conducted a numerical experiment using the process tracking model (Hashimoto et al., 2020) from December 18th to 19th, 2022. This model can diagnose particle characteristics by tracking the amounts of deposition growth and riming growth of ice particles as prognostic variables. The amounts of deposition growth are tracked separately in several classes with different ranges of temperature and humidity, which roughly represent different growth habits of snow crystals.
3. Results
Simulation results basically showed good agreement with observations, regarding satellite-observed cloud patterns and AWS-observed precipitation amounts. Moist air mass under the winter monsoon outbreak runned into the west coast of the Hokuriku district. Clouds and snowfall developed over the coastal area and extended over the Toyama plain. The air mass further runned inland and raised on the slope of Tateyama mountain range, where the clouds and snowfall developed again. In the coastal area and the upwind slope of the mountain range, riming growth considerably contributed to the snowfall amount. On the other hand, the deposition growth contributed differently to the snowfall amount depending on the ranges of temperature and humidity. The deposition growth in relatively warm temperatures mainly contributed to the snowfall on the upwind slope (western side) of the mountain range, while that in relatively cold temperatures contributed more on the downwind slope (eastern side). Generally, snow particles growing in warmer conditions flow lower in height compared to those growing in colder conditions, as temperature decreases with increasing height. In the simulation, the former snow particles were blocked by the mountain range of 2000 m or more, while the latter snow particles flowed over the mountain range. This result means that snow particles with different growth habits systematically fall on different geographical areas around a mountain range.
Acknowledgements
This work was supported in part by the Japan Society for the Promotion of Science KAKENHI grant number 22K03724, 20H04196, and 23H00729.
References
Hashimoto et al., 2020a: Process-Tracking Scheme Based on Bulk Microphysics to Diagnose the Features of Snow Particles. SOLA, 16, 51−56, doi:10.2151/sola.2020-009.
Hashimoto et al., 2020b: Numerical simulations on the mechanisms of snowfall associated with JPCZ in the 2018 winter. Proceedings of the 2020 autumn meeting of MSJ, PR-23. ( in Japanese)