EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

The substructure of extremely hot summers in the Northern Hemisphere

Matthias Röthlisberger, Michael Sprenger, Emmanouil Flaounas, Urs Beyerle, and Heini Wernli
Matthias Röthlisberger et al.
  • ETH Zürich, Institute for Atmospheric and Climate Science, Environmental Systems Science, Zürich, Switzerland (

In the last decades, extremely hot summers (hereafter extreme summers) have challenged societies worldwide through their adverse ecological, economic and public health effects. In this study, extreme summers are identified at all grid points in the Northern Hemisphere in the upper tail of the July–August (JJA) seasonal mean 2-meter temperature (T2m) distribution, separately in ERA-Interim reanalyses and in 700 simulated years with the Community Earth System Model (CESM) large ensemble for present-day climate conditions. A novel approach is introduced to characterize the substructure of extreme summers, i.e., to elucidate whether an extreme summer is mainly the result of the warmest days being anomalously hot, or of the coldest days being anomalously mild, or of a general shift towards warmer temperatures on all days of the season. Such a statistical characterization can be obtained from considering so-called rank day anomalies for each extreme summer, that is, by sorting the 92 daily mean T2m values of an extreme summer and by calculating, for every rank, the deviation from the climatological mean rank value of T2m.  

Applying this method in the entire Northern Hemisphere reveals spatially strongly varying extreme summer substructures, which agree remarkably well in the reanalysis and climate model data sets. For example, in eastern India the hottest 30 days of an extreme summer contribute more than 70% to the total extreme summer T2m anomaly, while the colder days are close to climatology. In the high Arctic, however, extreme summers occur when the coldest 30 days are substantially warmer than climatology. Furthermore, in roughly half of the Northern Hemisphere land area, the coldest third of summer days contribute more to extreme summers than the hottest third, which highlights that milder than normal coldest summer days are a key ingredient of many extreme summers. In certain regions, e.g., over western Europe and western Russia, the substructure of different extreme summers shows large variability and no common characteristic substructure emerges. Furthermore, we show that the typical extreme summer substructure in a certain region is directly related to the region’s overall T2m rank day variability pattern. This indicates that in regions where the warmest summer days vary particularly strongly from one year to the other, these warmest days are also particularly anomalous in extreme summers (and analogously for regions where variability is largest for the coldest days). Finally, for three selected regions, thermodynamic and dynamical causes of extreme summer substructures are briefly discussed, indicating that, for instance, the onset of monsoons, physical boundaries like the sea ice edge, or the frequency of occurrence of Rossby wave breaking, strongly determine the substructure of extreme summers in certain regions.

How to cite: Röthlisberger, M., Sprenger, M., Flaounas, E., Beyerle, U., and Wernli, H.: The substructure of extremely hot summers in the Northern Hemisphere, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4441,, 2020

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Presentation version 1 – uploaded on 15 Apr 2020
  • CC1: Comment on EGU2020-4441, Philipp Zschenderlein, 04 May 2020

    Hi Matthias,

    very nice and interesting work! They are really useful to understand the seaonsal cycle of extreme seasons and I think it would definitely be worth to apply this method to other variables. I have some questions:

    (1) Have you investigated when heat waves during otherwise normal summers occur? Do they occur more often during early-, mid-, or late-summer?

    (2) Maybe a more general question: How have you identified the 4 archetypical substructures? Couldn't there also be cases, where an extreme summer occurs, i.e. very intense heat wave, although many days are colder than normal?

    (3) In addition to my comment (2), have you tested more thresholds concerning your results on slide 6, because an upper-tercile for extreme hot summers seem to be quite low? It seems that for the grid point in eastern India the contribution of hot summer days would be more clear for higher percentages?




    • AC1: Reply to CC1, Matthias Röthlisberger, 05 May 2020

      Ciao Philipp,

      many thanks for your kind words and questions! I think you raise interesting points. Here are some replies:

      (1) No, we have not done so. In some sense, you are alluding to a „temporal substructure of extremely hot (or benign) summers“. I completely agree that assessing this temporal substructure would also be worthwhile and might help to better understand how extremely hot (or benign) summers differ from year to year and across space.

      (2) We do not objectively identify the archetypical substructures, those are just meant to illustrate how summers might differ with regard to their substructure. However, Slides 7 & 9 indicate which type of substructure is occurring where. For example, in regions where the contribution from the hottest tercile of summer days strongly exceeds the contribution from the coldest tercile, extreme summers mainly arise from heat waves. Conversely, in regions where the contribution from the coldest tercile of summer days makes up most of the anomaly, heat waves are of minor importance to the formation of extremely large positive seasonal mean anomalies. 

      You are completely right, relatively warm summers can occur due to a single heat wave, even if parts of the summer are colder than climatologically. In the paper we give an example of such a case (summer 1995 in Paris, Figure 4d).

      (3) I am not entirely sure I correctly understand this question. The terciles refer to terciles of summer days within a particular summer and are not used to identify a particular summer as an extreme. „Extremely hot summers“ are defined in ERAI as the top 5 summers of the last 40 years (i.e., 12.5%) and as the top 5% of summers in 700 years of CESM simulations (top 5%). Arguably, in particular for ERAI it is questionable to what extent these top 5 summers are indeed „extreme“ from a statistical point of view (low probability of occurrence). However, we chose this approach simply because there are so few data points on the seasonal time scale. 

      We have also performed the same analysis using deciles instead of terciles. Indeed, in some regions, the hottest or coldest decile of summer days already makes up a substantial fraction of the total seasonal mean anomaly.

  • CC2: Comment on EGU2020-4441, Theodore Shepherd, 05 May 2020

    Your results would seem to be interpretable in terms of skewness changes in the temperature PDFs, I would think. It would be interesting to compare with that perspective. Talia Tamarin-Brodsky has a paper coming out soon (I am a co-author) in Nature Geoscience on the role of skewness changes in the response of temperature variability in the NH to climate change, please look out for that!

    • AC2: Reply to CC2, Matthias Röthlisberger, 05 May 2020

      Thank you for this remark and for pointing to this new paper, I'll be happy to read it once it is available. Indeed, the skewness of the underlying daily temperature distribution shapes the substructure of extreme summers. This is noteworthy as it emphasizes that for understanding seasonal temperature extremes, a great deal can be learned from understand the physical processes that lead to skewed daily temperature distributions. However, there are also cases of extremely hot summers whose substructure is at odds with the climatological shape of the underlying daily temperature distribution, the summer 2010 in western Russia being a prominent example.

      • CC3: Reply to AC2, Theodore Shepherd, 05 May 2020

        That's interesting. In Talia's paper, we account for the skewness based on horizontal advection and the regional warming patterns, so as to focus on that aspect (which we feel has been underexamined in the event attribution literature). We look at 850 hPa but also examine the extent to which this is a good predictor of surface temperature. There are definitely going to be cases where local processes (especially land surface processes) have a large effect, and the Russian 2010 heat wave would surely be such a case.

        • AC3: Reply to CC3, Matthias Röthlisberger, 06 May 2020

          Interesting, I'm curious to read about this extension of Talia's 2019 J. Climate paper (which we by the way cite in our paper)! Thank you!