Predicting new snow density in the Italian Alps: A variability analysis based on 10 years of measurements

• DOI: 10.1002/hyp.13249
• Publication Date: 2018-08-01T12:33:23Z
• Authors: Mauro Valt; Nicolas Guyennon; Franco Salerno; Anna B. Petrangeli; Rosamaria Salvatori; Paola Cianfarra; Emanuele Romano
• Keywords: Snowpack; Orography; Explained variation

Abstract Despite its strong impact on the time evolution of snowpack, current estimation new snow density ( ρ hn ) is usually accomplished either by using local empirical techniques or assuming a constant density. Faced with lack an model valid for wide spatial scale and supported suitable number observations, this study aims to develop simple monthly linear regression models at entire Italian Alpine chain based 12,112 snowfall observations 122 stations, only air temperature as predictor. Moreover, remaining variance investigated in both space, also considering some qualitative features events. The daily measurements present mean value 115 kg m −3 (105 159 dry wet conditions, respectively). 24 hr preceding event has been found be best predictor , within 31% uncertainty. analysis associated residues allows supporting idea that adoption more approach than one analysed here not able substantially increase predictive capabilities model. In fact, main factor explaining over wind, but complex orography, mountain regions are, supplying realistic wind fields particularly challenging. Therefore, we conclude good choice estimating chain, well regional scale.