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Increasing probability of record-shattering climate extremes


Recent climate extremes have broken long-standing records by large margins. Such extremes unprecedented in the observational period often have substantial impacts due to a tendency to adapt to the highest intensities, and no higher, experienced during a lifetime. Here, we show models project not only more intense extremes but also events that break previous records by much larger margins. These record-shattering extremes, nearly impossible in the absence of warming, are likely to occur in the coming decades. We demonstrate that their probability of occurrence depends on warming rate, rather than global warming level, and is thus pathway-dependent. In high-emission scenarios, week-long heat extremes that break records by three or more standard deviations are two to seven times more probable in 2021–2050 and three to 21 times more probable in 2051–2080, compared to the last three decades. In 2051–2080, such events are estimated to occur about every 6–37 years somewhere in the northern midlatitudes.

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Fig. 1: Illustrative example of a simulated record-shattering event in Central North America.
Fig. 2: Drivers of record-shattering heatwave.
Fig. 3: Projected occurrence of record-shattering extremes in northern midlatitudes.
Fig. 4: Path-dependence of occurrence of record-shattering extremes.

Data availability

All original CMIP5 and CMIP6 data, the CanESM2 and NCAR LENS ensembles, and the ERA5 reanalysis used in this study, are publicly available as follows: CMIP5 model data,; CMIP6 model data,; CanESM2 ensemble reanalysis,; NCAR LENS ensemble,; and ECMWF5 ERA5 reanalysis,!/dataset/reanalysis-era5-single-levels. The output from CESM1.2 and CESM-CAM4 used in this analysis is available at

Code availability

All computer code to reproduce the main results and all figures are available at


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We acknowledge funding received from the Swiss National Science Foundation (grant no. 200020_178778) (E.M.F). We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP5 and CMIP6. We thank the climate modelling groups for producing and making available their model output. We acknowledge Environment and Climate Change Canada’s Canadian Centre for Climate Modelling and Analysis for executing and making available the CanESM2 large ensemble simulations. We acknowledge the US CLIVAR working group on large ensembles for compiling the Multi-Model Large Ensemble Archive.

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Authors and Affiliations



E.M.F and R.K designed the study. E.M.F. performed the model analysis and S.S. implemented the analytical solution. All authors contributed to the interpretation of the results and the writing of the manuscript.

Corresponding author

Correspondence to E. M. Fischer.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Raphaël Huser and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Observed record-shattering events.

Regional average Tx7day time series for (top) the European 2003 heatwave region 35–60°N and 10°W-20°E, (middle) the CNA region used in Fig. 1, (bottom) the Russian 2010 heatwave region 40–70°N and 20–70°E. The solid line shows a regional average of EOBS v19 gridded observations38 and the dashed lines of ERA5 reanalysis product39. The two dots illustrate two record-shattering events, and the magnitude is expressed in standard deviations of the detrended time series.

Extended Data Fig. 2 Changing return levels in other large ensemble.

Same as Fig. 1b but based on CanESM2 large ensemble. Yellow, orange and dark red lines illustrate the non-stationary GEV estimates for 200-, 500-, and 1000-yr return periods from all members using global mean temperature as a covariate for the location and scale parameter (see Methods). Best estimate of 1000-yr return period estimated from a stationary GEV fit from all 50 members (dotted violet line) (1950–2019) along with 95% CIs.

Extended Data Fig. 3 Observed heatwaves and their drivers.

(a-c) Tx7day anomaly and (d-f) associated 500 hPa geopotential during the 2003 European summer heatwave, the 1995 Chicago heatwave and the 2010 Russian heatwave. Anomalies are calculated based on the ECMWF ERA5 reanalysis and expressed as anomalies relative to the period 1986–2005.

Extended Data Fig. 4 Record-shattering event in long-term context.

(top) Tx7day anomalies averaged across Central N America in all CESM1.2 members from 1850–2100. The red and yellow dots illustrate the two record-shattering events discussed in the main text. The red line and red dot highlight the event and corresponding simulations shown in Fig. 1a. The yellow line and yellow dot highlight the second most extreme record-shattering event. (bottom) The second most intense record-shattering event discussed in the main text is illustrated in the same way as the most extreme event in Fig. 1a. Best estimate of 1,000-yr return period estimated from a stationary GEV fit to the selected member (1850–2019) (dashed turquoise line) and from all 84 members (dotted violet line) (1950–2019) along with 95% CI.

Extended Data Fig. 5 Drivers of record-shattering extremes in long-term context.

Same as Fig. 2d–g but relative to a constant reference period expressed as the multimember average across 1981–2010. The record-shattering extremes exceeding the previous record by more than 2σ, 3σ, and 4σ are marked with yellow, orange and red dots, respectively.

Extended Data Fig. 6 Examples of record-shattering events in other large ensembles and other regions.

Record-shattering event (red dot) and annual maximum 7-day temperature anomalies averaged over (a,c,e) Central N America) and (b,d,f) Central Europe in the corresponding simulation before the event (black line).

Supplementary information

Supplementary Information

Supplementary Text, Tables 1 and 2, Figs. 1–7 and References.

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Fischer, E.M., Sippel, S. & Knutti, R. Increasing probability of record-shattering climate extremes. Nat. Clim. Chang. 11, 689–695 (2021).

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