Increase of the energy available for snow ablation in the Pyrenees (1959-2020) and its relation to atmospheric circulation

Abstract

[eng] Mid-latitude mountain snowpacks are highly vulnerable to climate warming. Past and future hydroclimate changes require a thorougout knowledge of snow ablation physical processes and the associate climate drivers. In this work we provide the first spatio-temporal characteritzation of the energy available for snow ablation (Qm) in the Pyrenees for the period 1959–2020, during the main ablation season (March to June) for low (1200 m), mid (1800 m) and high (2400 m) elevations. We analyze the role of the the main Circulation Weather Types (CTs) in the Qm components for the entire mountain range. Finally, we train and tune a machine learning algorithm, the Random Forest, with atmospheric data (Surface Level Pressure and 500 hPa Geopotential Height) as an independent variable and Qm as the dependent one, in order to determine how much of the observed changes in Qm can be related with atmospheric circulation variability. The largest contribution of Qm is Net Radiation (Rn), increasing with elevation. Qm has shown a statistically significant increase since the 1980s. The comparison between the period 1959–1980 and the 2000–2020 revealed that positive Qm fluxes have been anticipated 22 and 12 days at mid and high elevations, respectively, showing evidence of an advance in the timing of the ablation season and faster snow ablation in high-elevation areas of the Pyrenees. The Qm is principally driven by Rn during the prevailing antyciclonic situations, characterized by the extension of high-pressure systems, lowbarometric gradients and the SE advection of hot and dry air masses. The positive frequency of these anticyclonic CTs explains the majority (75%) of the Qm variability, the upward Qm trends and the earlier snow ablation onset since the 1980s.