Modelling cold firn evolution at Colle Gnifetti, Swiss/Italian Alps

Abstract

The existence of cold firn and ice within the European Alps provides an invaluable source of palaeoclimatic data with the capability to reveal the nature of anthropogenic forcing in western Europe over the preceding centuries. Unfortunately, continued atmospheric warming has initiated the thermal degradation of cold firn to that of a temperate firn facie, where infiltrating meltwater compromises this vital archive. However, there is currently limited knowledge regarding the transition of firn between these different thermal regimes. Here, we present the application of a modified version of the spatially distributed Coupled Snow and Ice Model in Python (COSIPY) to the high-altitude glacierised saddle of Colle Gnifetti (CG; 4452 m a.s.l.) of the Monte Rosa massif, Swiss/Italian Alps. Forced by an extensively quality-checked meteorological time series from the Capanna Margherita (CM) station, with a distributed accumulation model to represent the prevalent on-site wind-scouring patterns, the evolution of the cold firn’s thermal regime is investigated between 2003 and 2023. At the saddle point (SP), our results show surface melt increasing at a rate of 0.53 cm w.e. yr−2 – representing a doubling over the 21-year period. This influx of additional meltwater and the resulting latent heat release from refreezing at depth drive englacial warming at a rate of 0.051 °C yr−1, comparable to in situ measurements. Since 1991, a measured warming of 1.5 °C (0.046 °C yr−1) has been observed at 20 m depth with a strong inversion in the temperature gradient developing in the last decade through the 18–30 m depth range of the glacier – also partially reproduced by our model. In lower-altitude regions (∼ 4300 m a.s.l.), simulated warming is much greater than the local rate of atmospheric warming, resulting in a rapid transition from cold to temperate firn – potentially indicative of future conditions at the saddle point of Colle Gnifetti. However, simulated firn temperatures are particularly sensitive to the parameterisations for modelling albedo and preferential percolation in this cold-temperate transition area.