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Extreme events

Wilder rainfall swings make record storms more likely

de Vries I, Sippel S, Zeder J, et al. · Communications earth & environment · 2024

Open access · cc by · source: Europe PMC

Future record-shattering daily downpours become much more probable because extreme-rain variability grows, not only because the mean inches up.

Study at a glance

Design
Computational / modelling — 100-member CESM2-LE analysis of record-shattering daily extremes under SSP3-7.0
N
N=100 · 100-member CESM2 large ensemble (other CMIP6 ensembles as checks)
Population
Land daily precipitation extremes in CESM2 large-ensemble climate projections
Outcome
Record-shattering extreme-rain probability driven by growing variability vs mean shifts

Structured fields used in claim comparison tables when every cited study has a complete layer.

Key findings

Record-shattering 5yRx1d probability rises over most land. In some tropics the late-21st-century probability ratio reaches 15. Variability (σ) changes dominate CESM2-LE in most regions, though other CMIP6 models have more balanced mean and variability terms. A CESM2 event physically resembles the 2021 western European floods, which exceeded a 1000-year return level in observations.

Methodology

Using the 100-member CESM2 large ensemble under SSP3-7.0, the authors tracked 5-year block-maximum daily precipitation (5yRx1d) that beat each member’s own record by at least one 1850–1949 standard deviation, compared that with a stationary climate, and split mean versus variability contributions; other CMIP6 ensembles provided a check.

Limitations

CESM2 has high climate sensitivity and SSP3-7.0 is a high-warming path, so ratios may be upper-end. Extreme-precipitation statistics remain uncertain, observations are short, and tropical mean and variability are still underestimated in models.

How this study connects

Role on claims

Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.

  • SupportsExtreme eventsconcept

    This library holds 5 empirical papers on extreme events with measured outcomes rather than reviews.

    Evidence for the claim as stated.

  • SupportsExtreme eventsconcept

    Future record-shattering daily downpours become much more probable because extreme-rain variability grows, not only because the mean inches up.

    Evidence for the claim as stated.

  • A 100-member CESM2 large ensemble under SSP3-7.0, checked with other CMIP6 ensembles, finds that record-shattering 5-year block-maximum daily rain (beating each member’s own record by ≥1 1850–1949 standard deviation) becomes more likely over most land. In some tropics the late-21st-century probability ratio reaches 15. Variability (σ) changes dominate CESM2-LE in most regions, while other CMIP6 models split mean and variability more evenly. A CESM2 analogue resembles the 2021 western European floods, which exceeded a 1000-year return level in observations.

    Evidence for the claim as stated.

  • Single-model large ensembles and the CMIP multimodel archive disagree about where uncertainty lives. CESM2-LE attributes most extra record-shattering rain to variability changes; other CMIP6 models are more balanced between mean and σ, and CESM2’s high climate sensitivity plus SSP3-7.0 make the probability ratio of 15 an upper-end figure. The CMIP5/6 extremes paper finds similar regional-mean sensitivity across generations but, at +1.5 °C, larger regional- than global-sensitivity uncertainty. Opening CESM2-LE is not the same as opening CMIP6.

    Evidence for the claim as stated.

  • SupportsEnsemble Simulationmethod

    Large ensembles can separate a change in the mean from a change in variability. In CESM2’s 100-member SSP3-7.0 set, the probability of record-shattering 5-year block-maximum daily rain rises over most land; in some tropics the late-21st-century probability ratio reaches 15, and variability (σ) changes dominate CESM2-LE in most regions while other CMIP6 models split mean and variability more evenly.

    Evidence for the claim as stated.

  • SupportsEnsemble Simulationmethod

    Single-model large ensembles and CMIP multi-model ensembles disagree about where uncertainty lives. CESM2-LE attributes most extra record-shattering rain to variability changes; the CMIP5/6 extremes paper finds similar regional mean sensitivity across generations and, at +1.5 °C, larger regional- than global-sensitivity uncertainty. Which ensemble you open changes whether you emphasise σ or the transient climate response.

    Evidence for the claim as stated.

Open questions

Tensions this paper is part of

From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.

  • Scope difference — different assays, populations, or outcomes

    Single-model large ensembles and the CMIP multimodel archive disagree about where uncertainty lives. CESM2-LE attributes most extra record-shattering rain to variability changes; other CMIP6 models are more balanced between mean and σ, and CESM2’s high climate sensitivity plus SSP3-7.0 make the probability ratio of 15 an upper-end figure. The CMIP5/6 extremes paper finds similar regional-mean sensitivity across generations but, at +1.5 °C, larger regional- than global-sensitivity uncertainty. Opening CESM2-LE is not the same as opening CMIP6.

  • Scope difference — different assays, populations, or outcomes

    Single-model large ensembles and CMIP multi-model ensembles disagree about where uncertainty lives. CESM2-LE attributes most extra record-shattering rain to variability changes; the CMIP5/6 extremes paper finds similar regional mean sensitivity across generations and, at +1.5 °C, larger regional- than global-sensitivity uncertainty. Which ensemble you open changes whether you emphasise σ or the transient climate response.

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Same topic cluster — not a recommendation engine.