the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Subseasonal prediction of compound heat and drought events
Abstract. Compound heat and drought events have severe socio-economic impacts on human health, agriculture and electricity supply. While these compound extremes are projected to intensify under climate change, our understanding of their subseasonal predictability remains limited compared to that of individual heat or drought events. In this study, we evaluate the predictability of compound heat and drought events over Europe using the subseasonal prediction system of the European Centre for Medium-Range Weather Forecasts (ECMWF). We find that the physical coupling between heat and drought contributes up to 10 % towards an increase in forecast skill when heat and drought co-occur, relative to a baseline that assumes independence between extremes. However, in regions where the physical coupling between heat and drought via land-surface interaction is misrepresented, compound skill can be lower than when drought are predicted in isolation. These findings highlight the critical role of accurately simulating land-surface feedbacks to improve the reliability of the subseasonal prediction for compound extremes.
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Status: open (until 24 Jun 2026)
- RC1: 'Comment on egusphere-2026-2465', Anonymous Referee #1, 04 Jun 2026 reply
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The manuscript "Subseasonal predictability of compound heat and drought events in Europe" by Wu and co-authors presents the predictability of compound heat and drought events in summer by the ECMWF models. The article is concise and dedicates most of the space to introduce clearly the methods used to evaluate the predictability and the role of the atmosphere-land coupling is the skill obtained. I think the article is well structured, clear and fits in the scope of the journal. I only have minor comments to the authors:
Appendices: Could you please reorder the appendices (first C, second B, third A, fourth D) so the first one introduces is number A?
Figures C1-C3: Could you please reduce the blank spaces between figures (this also applies to figure 1, 4 and 5)
Line 131: I'd rather use forecast as the past participle, instead of forecasted
Lines 209-210: Interestingly, this only happens for positive biases. Regions with negative biases show fair skill. Any comment on this?
Figure 6: Could you put the legend outside panel a and increase its font size? Could you also increase the font size of correlations in all panels? I struggle to read the values there. This also hold for figure D1