Abstract

AbstractRainfall and snowfall differ greatly in terms of their effects on hydrological processes. Snowfall is usually regarded as snow water equivalent in studying precipitation extremes, without considering the difference between snowfall and rainfall. Although snowfall is a key indicator of global change, no generally accepted and no unified indices for the assessment of snowfall extremes currently exist. The objectives of this study are to identify a suite of extreme snowfall indices that can be used to describe extreme snowfall events, and to analyse the dynamic changes in the extreme snowfall indices that have occurred in the Songhua River Basin (SRB), China. The study employs a dataset that contains daily data from 60‐meteorological stations that cover a 55‐year period. The results include a suite of extreme snowfall indices that can be used to assess extreme snowfall events. These extreme snowfall indices include four comprehensive indices, four intensity indices, four grade indices and two date indices. The total snowfall, the number of snowfall days, the ratio of snowfall to total precipitation, the snowfall intensity (SNI), the amounts of extreme snowfall and very extreme snowfall display insignificant trends over the entire SRB. The changes in the ending snowfall date exhibit a significant advancing trend (p < .001), while the changes in beginning snowfall date display a significant delaying trend (p < .05), which have led to a reduced snowfall season length (p < .001). These results provide a series of reference indices in describing snowfall extremes and they can enhance our understanding of the variations in snowfall that occur under global warming.

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