EGU2020-2123
https://doi.org/10.5194/egusphere-egu2020-2123
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Case Study of Blowing Snow Potential Diagnosis with Dynamical Downscaling

Seika Tanji1 and Masaru Inatsu2
Seika Tanji and Masaru Inatsu
  • 1Hokkaido University, Graduate school of science, Natural History Sciences, Sapporo, Japan (seika@sci.hokudai.ac.jp)
  • 2Hokkaido University, Faculty of science, Natural History Sciences, Sapporo, Japan (inaz@sci.hokudai.ac.jp)

Blowing snow potential is diagnosed for typical cases in roads around Sapporo, Japan, as snow concentration and visibility based on dynamically downscaled data with 1-km resolution. The results are consistent with the blowing-snow records on time and place of traffic disruption, when the dynamical downscaling (DDS) reproduced wind speed well for a case. Moreover, the DDS-based diagnosis had a strength on the onset and cease of blowing snow in the event. The diagnosis with mesoscale model analysis with 5-km resolution does not reproduce the blowing snow events in most area, however. Hence, the DDS potentially, not perfectly, adds the value to estimate blowing snow potential, despite a large scale-gap from an explicit representation of small-scale turbulence related to blowing snow. The meteorological forecast with 1-km resolution might improve the estimate of blowing snow potential.

How to cite: Tanji, S. and Inatsu, M.: Case Study of Blowing Snow Potential Diagnosis with Dynamical Downscaling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2123, https://doi.org/10.5194/egusphere-egu2020-2123, 2020

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