the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 01 Oct 2025
Global escalation of more frequent and intense compound heatwave-extreme precipitation events
Abstract. Compound heatwave-extreme precipitation (CHWEP) events, the rapid succession of heatwaves and extreme precipitation, pose growing compound and cascading risks. However, global-scale comparisons of their spatiotemporal evolution against single extremes remain limited. This study systematically examines the changes in CHWEP and corresponding single extremes from 1980 to 2100 using climate observations and projections under SSP (Shared Socioeconomic Pathway) 2–4.5 and SSP5-8.5 scenarios. We find that CHWEP exhibit higher frequency, stronger precipitation, and longer heatwave duration in mid-to-high latitudes, while tropical CHWEP feature more intense heatwaves than single heatwave events. These spatial contrasts persist in future projections. Under both scenarios, CHWEP and single extreme metrics intensify globally by 2056–2100, with post-heatwave precipitation exceeding that of single precipitation extremes, particularly under SSP5-8.5, highlighting sensitivity to greenhouse forcing. Critically, the co-occurrence is non-random, indicating an emerging physical linkage. In the tropics, the likelihood of extreme rainfall following heatwaves increases markedly. Our findings demonstrate that CHWEPs are evolving into a distinct, intensifying hazard class, necessitating their integration into climate resilience, early warning, and adaptation frameworks.
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Status: open (until 11 Dec 2025)
- RC1: 'Comment on egusphere-2025-4289', Anonymous Referee #1, 23 Oct 2025 reply
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CC1: 'Comment on egusphere-2025-4289', Marta Moreels, 15 Nov 2025
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The method of this study raises some questions for me. They use three reanalysis datasets
(ERA5, MERRA-2, JRA-55) as historical data and use four CMIP6 models under two SSP
scenarios for the future. Firstly, they address the systematic biases between climate model
simulations and reanalysis data. They highlight that they performed a simple bias correction
on the CMIP6 model output although, they note that, since they are comparing CHWEP
events and single extreme events, the precise accuracy of the absolute value is not
important for the conclusion. However, this is too short of an explanation in my opinion.
Limitations of the bias correction method and explaining it shortly would be more complete.Citation: https://doi.org/10.5194/egusphere-2025-4289-CC1
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The authors present an analysis of compound heatwave extreme precipitation (CHWEP) events using statistics computed an ensemble of 3 reanalysis data (in the past) and 4 CMIP models (for projection). They first show the differences on several statistics between CHWEP and single heat waves (SH). Then, they show how these statistics vary in the future, under several SSPs.
Overall, I found that this analysis suffers from several methodological issues that are detailed below. The paper is not very well written, with important quantities not properly defined, equations I could make sense of, etc. In my opinion, this work cannot be accepted for publication in HESS, unless completely reworked.
Main comments:
1. Currently, the authors compute the statistics in the past on reanalysis and in the future on climate models. It is well known that climate models are highly biased if not corrected with bias correction methods (see eg François et al., 2020). Is it the case here?
If the answer is 'no', then I don't see how it is possible to draw any definitive conclusions when comparing the future (using CMIP models) and the past (with reanalysis ) as done in Sections 4.2 and 4.3 (Figures 6 - 10 and S3 - S4). If the answer is 'yes', the authors should nevertheless first check that the WRT does not reject the equality of the distribution when the statistics are computed on the models during the past periods. This is a preliminary study that is absolutely necessary. Otherwise, one does not know for sure whether the differences observed are due to climate change or to differences between models and reanalysis.
2. Equations (1) - (8) are unclear. For example, in Eq. (1), there is a sum indexing over $i$, but I don't understand what the index is exactly (and there is no $i$ in CHWEP). Also I don't understand what we are summing exactly. Eq. (3) is even less clear. What is actually computed? The mean (over all events) of the sum of the temperature (withing each events)? In this case, one should see numbers above 100? I am really lost here.
The same kind of criticism could be made for each equation. Note also that these statistics are computed on a 45 year period, across several members of an ensemble. I guess there is some sort of averaging over the years that should be made apparent.
Equation (10) is also very unclear). Why is $P_{rand}$ a coincidence probability?
3. The authors do not explain how the ensembles are taken into account in their study. Are the above statistics computed on each member of the ensemble averaged out? Why is the number of members is different for the climate models than for the reanalysis? Does it pose a problem?
4. The vocabulary is not consistent throughout the paper. For example, according to line 127, $F_C$ and $F_S$ denote frequencies (hence the $F$ letter), but Figure 2(a) and 2(b) show counts. Note also that according to caption, Figures 2c and 2d show heatwave intensity (between 0 and 40 °C). Why "intensity", and not "temperature"? Note also that according to Eqs. (3) and (4), $IT_C$ and $IT_S$ are means over sums, which I expect to be above 100°C?
5. The test used in this study is the Wilcoxon rank-test (WRT), which is consistent under specific assumptions on the two distributions (say $X$ for a statistic computed in the past, and $Y$ for the same statistics computed in the future). The WRT is consistent if the alternative is that $Y$ is stochastically larger than $X$, i.e. $P(Y* > X*) \geq P(X* > Y*)$, where $X*$ and $Y*$ are random values from $X$ and $Y$, respectively. The test on the median (line 139) is consistent with the additional assumption of that alternative is restricted to a shift in location, i.e. $F_Y(s) = \delta + F_X(s)$, with $\delta >0$.
In any case, it is misleading to state that "the WRST is emplyed to assess differences in extreme events characteristics" (line 135-136). The authors should reformulate and be more specific (and narrow).
6. Section is almost impossible to follow; the authors compare quantities that have not been properly defined, such as standard deviations SD (line 242), "ratio of observed to random probability" (line 243). I could not make any sense of this.
Other comments:
Line 110: "The threshold for future periods is determined based on the threshold of historical period" is unclear to me. Does it mean they are equal? If not, what is formula to go from the threshold in the past to that in the futyre?
Caption of Figure 1: "Identification ...events"
Line 167: One could argue that single heat waves are prevalent in all desert regions, where it only rains when it gets cooler
Caption of all Figures: change "frequency" to "count"
Line 242, how are the standard deviations computed?
Caption of Figure 7: reference to panel (c) is missing