Case Study of Blowing Snow Potential Diagnosis with Dynamical Downscaling

Abstract

Blowing snow potential is diagnosed for typical cases 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. 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. Sensitivity tests clarify that blowing snow requires strong wind and freezing temperature at the surface.(Citation: Tanji, S., and M. Inatsu 2019: Case study of blowing snow potential diagnosis with dynamical downscaling. SOLA, 15, 32−36,

Two Different Pathways toward Convective Self-aggregation in Radiative-convective Equilibrium Simulations between SCALE and VVM

“…The radiative processes are treated with a k-distribution-based broadband radiation transfer model (Mstrn-X, Sekiguchi and Nakajima, 2008). SCALE has been used in studying the impacts of cloud microphysics on convection (Sato et al, 2015(Sato et al, , 2018, data assimilation (Honda et al, 2018(Honda et al, , 2019, regional climate changes (Adachi et al, 2019), severe weather events (Yoshida et al, 2019), the parameterization of physical processes (Iwabuchi and Okamura, 2017;Nishizawa et al, 2018), and dynamical downscaling of blowing snow events (Tanji et al, 2019;Inatsu et al, 2020).…”

The Blowing Snow Hazard Assessment and Risk Prediction model : a Python based downscaling and risk prediction for snow surface erodibility and probability of blowing snow

“…While a majority of blowing-snow parameterizations are implemented to simulate and predict snow transport on scales of 10-100 m, a few studies have adapted some aspects of blowing-snow prediction into mesoscale (1-100km) weather models to predict blowing-snow occurrence or visibility reductions (e.g., Bychova et al 2018;Tanji and Inatsu 2019). However, the parameterizations implemented in these studies do not use the comprehensive start-to-finish parameterizations implemented in snow transport models, nor do they account for snowpack history and erodibility in a robust way.…”