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We develop a unified statistical framework for attributing heatwaves as spatio-temporal phenomena under climate change. We quantify the impact of anthropogenic forcing on the probability and persistence of heatwaves not captured by standard…

应用统计 · 统计学 2026-04-30 Kamal Gasser , Johan Segers , Francesco Ragone

The modeling of spatio-temporal trends in temperature extremes can help better understand the structure and frequency of heatwaves in a changing climate. Here, we study annual temperature maxima over Southern Europe using a century-spanning…

统计方法学 · 统计学 2020-09-08 Peng Zhong , Raphaël Huser , Thomas Opitz

Extreme precipitation shows non-stationary behavior over time, but also with respect to other large-scale variables. While this effect is often neglected, we propose a model including the influence of North Atlantic Oscillation, time,…

大气与海洋物理 · 物理学 2022-11-09 Felix S. Fauer , Henning W. Rust

Accurate modelling of the joint extremal dependence structure within a stationary time series is a challenging problem that is important in many applications.\ Several previous approaches to this problem are only applicable to certain types…

统计方法学 · 统计学 2023-03-09 Graeme Auld , Ioannis Papastathopoulos

Numerical climate models are complex and combine a large number of physical processes. They are key tools in quantifying the relative contribution of potential anthropogenic causes (e.g., the current increase in greenhouse gases) on high…

应用统计 · 统计学 2020-05-19 Anna Kiriliouk , Philippe Naveau

Climate change has become a significant global concern due to its capacity to cause substantial disruption to daily life by increasing the frequency and intensity of extreme weather events. Given the rising trend of human interventions in…

应用统计 · 统计学 2026-04-28 Ritik Roshan Giri , Arnab Hazra

In recent years, the climate change research community has become highly interested in describing the anthropogenic influence on extreme weather events, commonly termed "event attribution." Limitations in the observational record and in…

The last decade has seen numerous record-shattering heatwaves in all corners of the globe. In the aftermath of these devastating events, there is interest in identifying worst-case thresholds or upper bounds that quantify just how hot…

数据分析、统计与概率 · 物理学 2025-01-24 Mark D. Risser , Likun Zhang , Michael F. Wehner

The task of simplifying the complex spatio-temporal variables associated with climate modeling is of utmost importance and comes with significant challenges. In this research, our primary objective is to tailor clustering techniques to…

应用统计 · 统计学 2023-11-21 Alexis Boulin , Elena Di Bernardino , Thomas Laloë , Gwladys Toulemonde

Changes in extreme weather events are a potentially important aspect of anthropogenic climate change (ACC), yet, are difficult to attribute to ACC because the record length is often similar to, or shorter than, extreme-event return periods.…

大气与海洋物理 · 物理学 2025-02-19 Peter Sherman , Peter Huybers , Eli Tziperman

Studying extreme events and how they evolve in a changing climate is one of the most important current scientific challenges. Starting from complex climate models, a key difficulty is to be able to run long enough simulations in order to…

大气与海洋物理 · 物理学 2017-12-27 Francesco Ragone , Jeroen Wouters , Freddy Bouchet

Extreme event attribution characterizes how anthropogenic climate change may have influenced the probability and magnitude of selected individual extreme weather and climate events. Attribution statements often involve quantification of the…

统计方法学 · 统计学 2018-02-06 Soyoung Jeon , Christopher J. Paciorek , Michael F. Wehner

Climate extremes such as floods, storms, and heatwaves have caused severe economic and human losses across Europe in recent decades. To support the European Union's climate resilience efforts, we propose a statistical framework for…

应用统计 · 统计学 2025-05-26 Carlotta Pacifici , Simone A. Padoan , Jaroslav Mysiak

Anthropogenic climate change (ACC) is altering the frequency and intensity of extreme weather events. Attributing individual extreme events (EEs) to ACC is becoming crucial to assess the risks of climate change. Traditional attribution…

大气与海洋物理 · 物理学 2024-08-30 Bernat Jiménez-Esteve , David Barriopedro , Juan Emmanuel Johnson , Ricardo Garcia-Herrera

Heatwaves are known to arise from the interplay between large-scale climate variability, synoptic weather patterns and regional to local scale surface processes. While recent research has made important progress for each individual…

大气与海洋物理 · 物理学 2023-05-25 Sebastian Buschow , Jan Keller , Sabrina Wahl

The analysis of extremes in climate models is hindered by the lack of statistics due to the computational costs required to run simulations long enough to sample rare events. We demonstrate how rare event algorithms can improve the…

大气与海洋物理 · 物理学 2021-07-07 Francesco Ragone , Freddy Bouchet

When extreme weather events affect large areas, their regional to sub-continental spatial scale is important for their impacts. We propose a novel machine learning (ML) framework that integrates spatial extreme-value theory to model weather…

应用统计 · 统计学 2025-05-29 Jonathan Koh , Daniel Steinfeld , Olivia Martius

Extreme events, such as wave-storms, need to be characterized for coastal infrastructure design purposes. Such description should contain information on both the univariate behaviour and the joint-dependence of storm-variables. These two…

Rapid changes in climatic conditions threaten both socioeconomic and ecological systems, as these might not be able to adapt or to migrate at the same pace as that of global warming. In particular, an increase of weather and climate…

大气与海洋物理 · 物理学 2020-06-14 Joan Rey , Guillaume Rohat , Marjorie Perroud , Stéphane Goyette , Jérôme Kasparian

We investigate the changing nature of the frequency, magnitude and spatial extent of extreme temperatures in Ireland from 1931 to 2022. We develop an extreme value model that captures spatial and temporal non-stationarity in extreme daily…

统计方法学 · 统计学 2023-04-03 Dáire Healy , Jonathan Tawn , Peter Thorne , Andrew Parnell
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