Extreme heatwaves could intensify much more than expected with climate change
In Winter 2023 I started planning my first research stay after many years. I was thrilled to work at the University of Reading with Reinhard Schiemann from the National Centre for Atmospheric Science. The plans were very loose: working on extreme events and atmospheric circulation. What mattered most: no distraction.
Over spring, a more specific focus emerged: do event attribution studies get the influence of climate change on the most devastating extreme events right? I was looking forward to a time to freely explore ideas. Reinhard is working in a project on single model initial condition large ensembles (SMILES). It was therefore clear that our research should build upon such models which are ideal to sample many realisations of very extreme events.
In Reading, I decided to focus on heat extremes as the event type with the clearest signal to noise ratio. One research question was rather technical, whether the 1-year block length typically chosen in block maxima approaches used for extrme event studies was sufficiently long. Yes, it turned out, at least by and large.
The other research question was one of basic research. Most studies on climatic changes in extreme events focus on moderately extreme events occurring once every few years or even several times per year. The most extreme and devastating events such as in Canada in 2021, India in 2022 or the Mediterranean in 2023, however, are very rare events. So far, the tacit assumption in climate change studies was that such extreme events respond similarly to climate change than moderate extreme events. Our hypothesis was that this assumption was wrong.
Already the first analyses - comparing the response of very rare 200-year heat events with that of moderate 2-year events - confirmed our hypothesis. We were thrilled finding that over large contiguous regions, 200-year events are projected to change much stronger than 2-year events. Over other regions, the reverse is projected, i.e., changes in 200-year events are dampened.
Some of these regions are large-scale bands, some are wave-like patterns, organised into dipoles of amplified and dampened trends of very extreme events. In any case, these patterns suggested some coherent physical mechanisms.
We of course knew that soil moisture temperature coupling played an important role in amplifying changes in heat extremes. So we did a quick analysis. Our temperature return level estimates were based on the hottest days in each year, so we extracted soil moisture - and later latent heat fluxes - on these days as well, and calculated correlations between these temperature and soil moisture values as a measure of coupling strength. Projected changes in this coupling showed the same spatial patterns as the differences in return level trends. Where the coupling increased, trends in 200-year events were
amplified, and vice-versa.
But it took a couple of iterations, literature research and analyses until we realised a key point: previous research has typically focused on seasonal mean coupling, while our results were based on coupling during the hottest days. Just recently, Hsu and Dirmeyer argued in Nature Communications, that coupling strength is not constant but varies with weather. So we hypothesised that coupling strength varies during heatwaves, and the coupling during the hottest days of a heatwave is what really matters for the trend modifications
we found. And indeed, the patterns and trends in this event coupling turned out to be markedly different from the patterns and trends in seasonal mean coupling.
Based on earlier work we built a conceptual model to identify the drivers of this change in event coupling. Coupling strength is high in a transitional soil moisture regime between very dry (soil moisture limited) and very wet (energy limited) conditions. Hence, changes in coupling strength should be related to present-day conditions as well as changes in soil moisture. The latter should be strongly influenced by projected precipitation changes. All these relationships could be found in the model simulations. Unfortunately, the considered climate models strongly disagree about the exact locations of the affected regions.
And here the circle is complete: precipitation trends are strongly dominated by changes in the atmospheric circulation, including substantial uncertainties. Thus, we finally ended up where we started: understanding the influence of the atmospheric circulation on very extreme events.
If our results stand up to further scrutiny, they may prove very relevant for climate risk assessments: In the regions, where changes in very rare extreme events are amplified compared to moderate extreme events, such assessments may have underestimated the worst future hazards arising from extreme heat. In turn adaptation planning may not have considered sufficient measures, e.g., for health prevention, agriculture or even infrastructure planning. In contrast, in those regions, where the strongest extremes are dampened, adaptation planning might have been too conservative and thus more costly as required. Future research thus should focus on building more robust knowledge about the underlying mechanisms and the affected regions.
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