Rarest rainfall events will see the greatest relative increase in magnitude under future climate change

Gründemann, Gaby; Giesen, Nick van de; Brunner, Lukas; Ent, Ruud J. van der

doi:10.1038/s43247-022-00558-8

Cited by 45 publications

(28 citation statements)

References 70 publications

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“…Given the close connection between the typical SPs and extreme rainfall at various timescales, we can better project the future changes in extreme rainfall by weighting the models based on their capability to capture the observed typical SPs in historical simulations. Many previous studies constrained extreme rainfall projections by directly using rainfall-based evaluation metrics (Gründemann et al, 2022;W. Li et al, 2016;B.…”

Section: Summary and Discussionmentioning

confidence: 99%

Summer Extreme Rainfall Over the Middle and Lower Reaches of Yangtze River: Role of Synoptic Patterns in Historical Changes and Future Projections

Hu,

Lin,

Deng

et al. 2023

JGR Atmospheres

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It is one of the major challenges in climate science to project future changes in extreme rainfall. To overcome this challenge, in this study, four typical synoptic patterns (SPs) triggering summer extreme rainfall over the middle and lower reaches of Yangtze River (MLYR) are identified through hierarchical clustering. These typical SPs share common characteristics of intensified Mei‐yu trough and Western Pacific Subtropical High but differ in terms of mid‐latitudes disturbances, such as an intensified ridge (Cluster 1, Cluster 2) or trough (Cluster 3, Cluster 4) near Lake Baikal (Cluster 1, Cluster 3) or Northeast China (Cluster 2, Cluster 4). The linkage between extreme rainfall and typical SPs is verified at various time scales. The typical SPs associated with extreme rainfall are substantially different from the circulation patterns found on ordinary days, and their frequency is significantly correlated with that of extreme rainfall across the interannual scales. Furthermore, the distinct changes in different typical SPs serve as a “bridge” for understanding the long‐term impact of circulation changes on local extreme rainfall, even though the two do not appear to be connected at first sight. Specifically, the circulation changes imply more (less) frequent SP‐Cluster 1 (SP‐Cluster 3), which tends to produce more extreme rainfall to the south (north) of the Yangtze River within MLYR. To project future changes in extreme rainfall, we utilize a weighting method for the multi‐model ensemble based on each model's capability to capture the observed typical SPs. This method effectively narrows the inter‐model spread.

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Section: Summary and Discussionmentioning

confidence: 99%

Summer Extreme Rainfall Over the Middle and Lower Reaches of Yangtze River: Role of Synoptic Patterns in Historical Changes and Future Projections

Hu,

Lin,

Deng

et al. 2023

JGR Atmospheres

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“…To do so, we use the generalized extreme value (GEV) distribution, a well-established statistical model to describe the maxima of temperature distributions (or maxima of any other time series data) (13). The GEV distribution has been applied to study, for example, extreme temperatures and precipitation on land (14)(15)(16)(17)(18). While there has been some application of the GEV in marine contexts (19,20), it remains underused in oceanic applications and, in particular, in studies of MHWs (21).…”

Section: Introductionmentioning

confidence: 99%

Historical and future maximum sea surface temperatures

Cael,

Burger,

Henson

et al. 2024

Sci. Adv.

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Marine heat waves affect ocean ecosystems and are expected to become more frequent and intense. Earth system models’ ability to reproduce extreme ocean temperature statistics has not been tested quantitatively, making the reliability of their future projections of marine heat waves uncertain. We demonstrate that annual maxima of detrended anomalies in daily mean sea surface temperatures (SSTs) over 39 years of global satellite observations are described excellently by the generalized extreme value distribution. If models can reproduce the observed distribution of SST extremes, this increases confidence in their marine heat wave projections. 14 CMIP6 models' historical realizations reproduce the satellite-based distribution and its parameters’ spatial patterns. We find that maximum ocean temperatures will become warmer (by 1.07° ± 0.17°C under 2°C warming and 2.04° ± 0.18°C under 3.2°C warming). These changes are mainly due to mean SST increases, slightly reinforced by SST seasonality increases. Our study quantifies ocean temperature extremes and gives confidence to model projections of marine heat waves.

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“…Global warming is known to intensify the water cycle, leading to an increase in climate extremes (Allen & Ingram, 2002; Easterling et al., 2016; IPCC, 2012). Historical data reveals increases in observed precipitation extremes (Alexander, 2016; Asadieh & Krakauer, 2015; Papalexiou & Montanari, 2019), and projections indicate further intensification in the future (e.g., Donat et al., 2016; Fowler et al., 2021; Gründemann et al., 2022; Meredith et al., 2019; Moustakis et al., 2021; Pendergrass & Knutti, 2018; Pfahl et al., 2017; Tandon et al., 2018; Westra et al., 2014). Yet, these patterns and shifts are not uniform across the world.…”

Section: Introductionmentioning

confidence: 99%

Historical Shifts in Seasonality and Timing of Extreme Precipitation

Gründemann,

Zorzetto,

van de Giesen

et al. 2023

Geophysical Research Letters

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Global warming impacts the hydrological cycle, affecting the seasonality and timing of extreme precipitation. Understanding historical changes in extreme precipitation occurrence is crucial for assessing their impacts. This study uses relative entropy to analyze historical changes in seasonality and timing of extreme daily precipitation occurrences on the global domain for 63 years of fifth generation of the European Reanalysis reanalysis data. Our analysis reveals distinct regional patterns of change. During the second half of the 20th century, Africa and Asia experienced high clustering of precipitation extremes. Over the past 60 years, clustering increased in Africa while becoming more spread out in Asia. North America and Australia had initially lower clustering and showed slight increases over time. Extreme events in extra‐tropical land regions mainly occurred in summer, with modest shifts in timing. These findings have implications for risk assessments of natural hazard like flash floods and landslides, emphasizing the necessity for region‐specific adaptation strategies.

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Rarest rainfall events will see the greatest relative increase in magnitude under future climate change

Cited by 45 publications

References 70 publications

Summer Extreme Rainfall Over the Middle and Lower Reaches of Yangtze River: Role of Synoptic Patterns in Historical Changes and Future Projections

Summer Extreme Rainfall Over the Middle and Lower Reaches of Yangtze River: Role of Synoptic Patterns in Historical Changes and Future Projections

Historical and future maximum sea surface temperatures

Historical Shifts in Seasonality and Timing of Extreme Precipitation

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