Future winter snowfall and extreme snow events in the Pyrenees

IF 4.5 2区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES Atmospheric Research Pub Date : 2025-01-03 DOI:10.1016/j.atmosres.2025.107912
Josep Bonsoms, Juan I. López-Moreno, Marc Lemus-Cánovas, Marc Oliva
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Abstract

Snowfall is a crucial climate variable in mountainous regions: it influences hydrological and ecosystem dynamics and has a major impact on socioeconomic activities. This study examines the future changes (2024 to 2100) in winter (December, January and February, included) snowfall and extreme snow events in the Pyrenees, using a high-resolution dataset (2.5 km) derived from multiple CMIP5 General Circulation Models (GCMs) under RCP4.5 and RCP8.5 greenhouse gas scenarios, forced with the SAFRAN model. Winter snowfall shifts are examined considering accumulated snowfall (SF), extreme snowfall (Percentile >95th; SF95) per season, and return period levels (RPs) based on fitting Generalized Extreme Value to annually maximum SF. The data indicate an overall decline in SF across the entire mountain range and at all elevations. Trend analysis reveals a statistically significant negative evolution of SF (Tau Mann-Kendall >0.3; p-value ≤0.05) for most of the mountain range under RCP8.5. Projections for the end of the 21st century (2080–2100 period) anticipate reductions ranging from −9 % (RCP4.5; 2500–3000 m) to −29 % (RCP8.5; 1000–1500 m) compared to the historical climate (1960–2006 period). SF95 projections range from +2 % (RCP4.5; 2500–3000 m) to −25 % (RCP8.5; 2500–3000 m) for the same periods. Annual maximum extreme snowfall RPs indicate decreases over the historical period, regardless of the scenario and elevation range. These changes are attributed to warming and declining precipitation (P), with maximum P reductions reaching reduction of −24 % for RCP8.5 (2080–2100 period). Differences among GCMs contribute to a variability of ±20 % around the average multi-model mean. These results anticipate major terrestrial ecosystem changes in the Pyrenees, including significant spatiotemporal changes in hydrological resources potentially affecting millions of people living in large lowland cities.
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比利牛斯山脉未来的冬季降雪和极端降雪事件
降雪是山区的一个重要气候变量:它影响水文和生态系统动态,并对社会经济活动产生重大影响。本研究利用来自多个CMIP5环流模式(GCMs)在RCP4.5和RCP8.5温室气体情景下的高分辨率数据集(2.5 km),在SAFRAN模式的强迫下,研究了比利牛斯山脉冬季(包括12月、1月和2月)降雪和极端雪事件的未来变化(2024 - 2100)。考虑累积降雪(SF)、极端降雪(百分位数>95;SF95),以及基于广义极值拟合年最大SF的回归期水平(RPs)。数据表明,整个山脉和所有海拔高度的SF总体下降。趋势分析显示SF呈显著负向演化(Tau Mann-Kendall >0.3;p值≤0.05)。对21世纪末(2080-2100年期间)的预估预计减少幅度为- 9% (RCP4.5;2500-3000 m)至−29% (RCP8.5;1000-1500米),与历史气候(1960-2006年)相比。SF95预测范围为+ 2% (RCP4.5;2500-3000 m)至- 25% (RCP8.5;2500-3000米)。在不同的情景和海拔范围下,年最大极端降雪RPs在历史时期呈下降趋势。这些变化归因于变暖和降水(P)减少,RCP8.5(2080-2100年)最大P减少量达到- 24%。gcm之间的差异导致了多模式平均值周围±20%的变率。这些结果预测了比利牛斯山脉陆地生态系统的重大变化,包括水文资源的重大时空变化,可能影响生活在大型低地城市的数百万人。
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来源期刊
Atmospheric Research
Atmospheric Research 地学-气象与大气科学
CiteScore
9.40
自引率
10.90%
发文量
460
审稿时长
47 days
期刊介绍: The journal publishes scientific papers (research papers, review articles, letters and notes) dealing with the part of the atmosphere where meteorological events occur. Attention is given to all processes extending from the earth surface to the tropopause, but special emphasis continues to be devoted to the physics of clouds, mesoscale meteorology and air pollution, i.e. atmospheric aerosols; microphysical processes; cloud dynamics and thermodynamics; numerical simulation, climatology, climate change and weather modification.
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