Identification of slushflow situations from regional weather models

Abstract

Slushflows are known phenomena that cause significant problems for settlements and infrastructure in Norway. Even though single events in the same location are rather rare compared to avalanches, slushflows do occur annually on a national scale. Both intensive snowmelt events as well as high amounts of rain on the snow cover can cause slushflows during the whole winter season. In recent years eight fatalities and widespread problems for infrastructure in Norway have increased the focus on slushflows. Early warning criteria based on readily available meteorological, hydrological and snow data need to be identified to allow a nationwide monitoring of potentially critical situations and corresponding locations that might lead to slushflow events. Earlier work focused on input data from meteorological stations. These stations are often located at sea level and give little information on the meteorological conditions in the release and drainage areas in the mountains. During the last decade, regional weather models have been developed that deliver weather prognosis every hour with up to 4 km grid resolution. In Norway, observed precipitation and temperature are interpolated to a one-kilometre grid and used to model snow conditions and snowmelt. This study aims at analysing the available data to identify critical meteorological elements and their thresholds for the release of slushflows. Examples from recent years will be studied also taking into account the development of the snow cover prior to the slushflow events. The results indicate that the available data has a promising ability to identify critical situations on a regional level.