Blowing Snow Forecast Using Numerical Atmospheric Model Output Data

Bychkova, V. I.; Kurbatova, M. M.; Zarochentsev, G.A.; Ignatov, R. Yu.

doi:10.3103/s1068373918070038

Cited by 2 publications

(1 citation statement)

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“…The threshold windspeed of dry snow is generally proportional to the temperature, with lower temperatures resulting in lower starting wind speeds [15]. However, when the temperature drops below −27.27 • C, the snow particles start to deteriorate, leading to an increase in the required starting wind speed [16]. Temperature is also a critical parameter affecting the shape of snow particles; −5 • C is the critical temperature at which snow crystals transition from plate-like to columnar [17].…”

Section: Introductionmentioning

confidence: 99%

Study on the Susceptibility of Drifting Snow in Ya’an–Qamdo Section of the Railway in Southwest China

Zhou,

Zhang,

Yang

et al. 2024

Applied Sciences

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To investigate the susceptibility of drifting snow along the Ya’an–Qamdo section of the railway, which is located in a high-altitude and cold plateau in Southwest China with scarce meteorological information, the Weather Research and Forecasting Model (WRF) is used in this paper to simulate the spatio-temporal distribution of meteorological data. According to the varying terrain, the railway section from Ya’an to Qamdo is divided into two regions along 100.8° E for double-layer nested simulation. The original land use data of the WRF model are used in region 1. Due to the increased number of mountains in region 2, the original data are replaced by the MCD12Q1v006 land use data, and the vertical direction layers are densified near the ground to increase simulation accuracy. The simulated results are compared with the observation data. It is found that after densification, the results have been significantly improved. The results obtained by the WRF model can accurately simulate the change trends of temperature, rainfall, and wind speed, and the correlation coefficients are relatively high, which verifies the accuracy of WRF for simulating complex terrain regions. The simulation results further indicate that approximately 300 km of the Ya’an–Qamdo railway may experience drifting snow. Among them, no drifting snow events occur in Ya’an County, and the areas with higher probability are located at the border between Luding County and Tianquan County, followed by Kangding area. The remaining areas have a probability of less than 10%. The WRF model demonstrates its capability in the drifting snow protection of railways with limited meteorological data.

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Section: Introductionmentioning

confidence: 99%