Analysis of Regional Difference in Altitude Dependence of Snow Depth Using High Resolve Numerical Experiments

Abstract

This study focuses on the main factor of regional difference in Altitudinal Dependency of Snow Depth (ADSD) and discusses the applicable range of snow cover estimation method with ADSD. We use the high-density surface observational data and a regional climate model in Niigata Prefecture. The estimation method with ADSD produces significant estimation error if the method is applied to broad areas. The high-density observational data show the regional difference of ADSD between windward and leeward areas with a coastal mountain. Numerical simulation reproduces these observational results. We evaluate mountain effects on the regional difference of ADSD using sensitivity experiments. In the sensitivity experiment, the altitude is changed from a mountain to a flat plain. The sensitivity experiment shows that the regional differences of ADSD are not simulated. The results indicate that the applicable range of the estimation method with ADSD is limited to a single slope and mountain. It should be noted that this method has a high probability of increasing the estimation error in

Changes in extremely heavy and light snow-cover winters due to global warming over high mountainous areas in central Japan

“…In heavy snow-cover years, winter precipitation clearly increases with elevation ( Fig. 8a), which is consistent with the findings of previous studies (e.g., Uno et al 2014;Asaoka and Kominami 2013). Winter precipitation will increase with the progress of global warming at all elevations.…”

Total dust deposition flux during precipitation in Toyama, Japan, in the spring of 2009: A sensitivity analysis with the NASA GEOS-5 Model

“…We have additionally speculated that the major difference in the simulated precipitation between EXP1 and EXP2 is critically dependent on how topography was resolved. A recent regional modelling study by Uno et al (2014) found that topography (i.e., altitude) effect was critical in simulating the precipitation (i.e., snow) distributions in a nearby region of Toyama prefecture in Japan, further supporting our speculation of the role of orographic forcing in governing the precipitation in Toyama. Chao (2012), on the other hand, points out that GCMs typically simulate excessive precipitation in the vicinity of steep terrain, which would be exacerbated in our higher resolution simulations, and A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPT Yasunari et al (2015), Atmospheric Research.…”

Stalled Improvement in a Numerical Weather Prediction Model as Horizontal Resolution Increases to the Sub-Kilometer Scale

“…Certain improvements in some aspects have been observed when the horizontal grid spacing is increased from about ten to several kilometers (e.g., Done et al 2004;Kain et al 2006;Weisman et al 2008;Duc et al 2013;Yashiro et al 2016). NWPs with even finer horizontal grid spacing (~1 km) are now often used for various research purposes including regional climatology (e.g., Uno et al 2014). Forecasts of fog in real cases have been shown to benefit from the finer horizontal grid spacing (333 m) (Boutle et al 2016).…”