Brief communication: A numerical tool for averaging large data sets of snow stratigraphy profiles useful for avalanche forecasting

Abstract. Snowpack models can provide detailed insight about the evolution of the snow stratigraphy in ways that is not possible with direct observations. However, the lack of suitable data aggregation methods currently prevents the effective use of the available information, which is commonly reduced to bulk properties and summary statistics of the entire snow column or individual grid cells. This is only of limited value for operational avalanche forecasting. To address this challenge, we present an averaging algorithm for snow profiles that can effectively synthesize large numbers of snow profiles into a meaningful overall perspective of the existing conditions. Notably, the algorithm enables compiling of informative summary statistics and distributions of snowpack layers, which creates new opportunities for presenting and analyzing distributed and ensemble snowpack simulations.