The observed evolution of sub-daily to multi-day heavy precipitation in Switzerland

IF 2 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Atmospheric Science Letters Pub Date : 2024-05-20 DOI:10.1002/asl.1240
Victoria M. Bauer, Simon C. Scherrer
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Abstract

Heavy precipitation is a major natural hazard in the Alps. Understanding the possible changes due to climate change is a prerequisite for effective climate adaptation and protection. In this study, we revisit the long-term (1901–2023) evolution of daily and multi-day heavy precipitation intensity and frequency, discuss trends for sub-daily to multi-day events in the recent period 1981–2023 and investigate elevation dependencies in the complex topography of Switzerland. We analyze station measurements from MeteoSwiss' dense operational network covering the whole country and a wide range of elevation levels. We find that daily maximum precipitation and the frequency of precipitation events exceeding the 99th all-day percentile have increased since 1901 with a peak in the 1980s and decreases thereafter. For the recent period 1981–2023, positive trends in summer heavy precipitation intensity are detected for short (10-min to 3-h) events, but no changes are found for the frequency of these moderate extreme events. For longer (1- to 5-day) events on the other hand, decreases in intensity and frequency are found, especially for the winter half-year. We hypothesize that the opposing trends on the centennial (1901–2023) vs. decadal (1981–2023) time scales are caused by the interaction between thermodynamics, reflecting the primary influence of human-induced climate change, and the internal variability of atmospheric dynamics. Moreover, we observe a small negative elevation dependency of the daily long-term trends up to 2300 m above sea level. For the 1981–2023 trends, no strong elevation dependencies are found for sub-daily events. For daily events, we find small opposing negative summer and positive winter elevation dependencies for both intensities and frequencies. The reason for these tendencies remains unclear. Our results underscore the need to further investigate the interplay between climate change, internal variability of large-scale dynamics and elevation to better understand heavy precipitation variability in the complex Alpine terrain.

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瑞士观测到的从亚日降水到多日强降水的演变过程
强降水是阿尔卑斯山的主要自然灾害。了解气候变化可能带来的变化是有效适应和保护气候的先决条件。在本研究中,我们重温了每日和多日强降水强度和频率的长期演变(1901-2023 年),讨论了最近 1981-2023 年期间次日至多日降水事件的趋势,并研究了瑞士复杂地形中的海拔依赖性。我们分析了瑞士气象局覆盖全国和各种海拔高度的密集运行网络中的站点测量数据。我们发现,自 1901 年以来,日最大降水量和超过全天百分位数第 99 位的降水事件频率一直在增加,并在 20 世纪 80 年代达到峰值,随后有所下降。在最近的 1981-2023 年期间,短时(10 分钟至 3 小时)夏季强降水强度呈正趋势,但这些中度极端事件的频率没有变化。另一方面,对于较长时间(1 至 5 天)的降水来说,降水强度和频率都有所下降,尤其是在冬半年。我们假设,百年(1901-2023 年)与十年(1981-2023 年)时间尺度上的相反趋势是由热力学与大气动力学内部变异性之间的相互作用造成的,热力学反映了人类引起的气候变化的主要影响。此外,我们还观察到,在海拔 2300 米以下,日长期趋势与海拔高度有微小的负相关。在 1981-2023 年的趋势中,亚日事件没有发现强烈的海拔依赖性。对于日事件,我们发现在强度和频率方面,夏季和冬季的海拔高度都有小幅相反的负相关关系。这些趋势的原因尚不清楚。我们的研究结果表明,有必要进一步研究气候变化、大尺度动态的内部变异性和海拔之间的相互作用,以便更好地了解阿尔卑斯山复杂地形的强降水变异性。
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来源期刊
Atmospheric Science Letters
Atmospheric Science Letters METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
4.90
自引率
3.30%
发文量
73
审稿时长
>12 weeks
期刊介绍: Atmospheric Science Letters (ASL) is a wholly Open Access electronic journal. Its aim is to provide a fully peer reviewed publication route for new shorter contributions in the field of atmospheric and closely related sciences. Through its ability to publish shorter contributions more rapidly than conventional journals, ASL offers a framework that promotes new understanding and creates scientific debate - providing a platform for discussing scientific issues and techniques. We encourage the presentation of multi-disciplinary work and contributions that utilise ideas and techniques from parallel areas. We particularly welcome contributions that maximise the visualisation capabilities offered by a purely on-line journal. ASL welcomes papers in the fields of: Dynamical meteorology; Ocean-atmosphere systems; Climate change, variability and impacts; New or improved observations from instrumentation; Hydrometeorology; Numerical weather prediction; Data assimilation and ensemble forecasting; Physical processes of the atmosphere; Land surface-atmosphere systems.
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