The Mediterranean (MED) Basin is a climate change hotspot that has seen drying and a pronounced increase in heatwaves over the last century. At the same time, it is experiencing increased heavy precipitation during wintertime cold spells. Understanding and quantifying the risks from compound events over the MED is paramount for present and future disaster risk reduction measures. Here, we apply a novel method to study compound events based on dynamical systems theory and analyse compound temperature and precipitation events over the MED from 1979 to 2018. The dynamical systems analysis quantifies the strength of the coupling between different atmospheric variables over the MED. Further, we consider compound warm–dry anomalies in summer and cold–wet anomalies in winter. Our results show that these warm–dry and cold–wet compound days are associated with large values of the temperature–precipitation coupling parameter of the dynamical systems analysis. This indicates that there is a strong interaction between temperature and precipitation during compound events. In winter, we find no significant trend in the coupling between temperature and precipitation. However in summer, we find a significant upward trend which is likely driven by a stronger coupling during warm and dry days. Thermodynamic processes associated with long-term MED warming can best explain the trend, which intensifies compound warm–dry events.
The Mediterranean (MED) Basin is considered a climate change hotspot
Many studies have investigated climate change projections over the MED under high greenhouse gas emission scenarios, providing strong evidence for a continuation of the trends witnessed in the historical period and much warmer and drier conditions by the end of the 21st century
In recent years, it has become increasingly clear that hydro-meteorological impacts often result from the compounding nature of several variables and/or events, even if they are not extreme when analysed independently
Here, we specifically seek to characterize precipitation–temperature compound events over the MED in terms of the coupling between precipitation and temperature fields. This allows us to relate long-term changes in compound events to their underlying physical drivers. We focus on compound warm–dry and cold–wet events during summer (June–July–August, JJA) and winter (December–January–February, DJF) respectively. We apply a method based on dynamical systems theory that reflects the dynamical evolution of the atmosphere and is well-suited to diagnosing changes in atmospheric properties
In this study, we use a dynamical systems approach to compute two metrics:
The calculation of the dynamical systems metrics stems from the combination of Poincaré recurrences with extreme value theory
To extend the analysis to two variables,
We further define the co-recurrence ratio
In order to compute the dynamical metrics we use a quantile
Finally, the dynamical systems approach rests on a number of theoretical assumptions, not all of which are strictly fulfilled by climate data. Specifically, the framework assumes the existence of an underlying chaotic attractor for the dynamics and was derived for ergodic systems
In our analysis, we consider each daily time step in our datasets in turn as the state of interest
We use the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis over 1979–2018, with a spatial horizontal resolution of 0.25
The statistical significance of the Sen's slopes
The statistical significance of SLP,
Lastly, we checked the statistical significance of the percentage (%) agreement between JJA (DJF) CDEs and compound events. Here, the null hypothesis is that the JJA (DJF) observed percentage agreement is due to chance, and to compute the significance the following steps have been followed: (i) create
During JJA, the co-recurrence ratio (
Co-recurrence ratio (
We next compute the local co-persistence (
As Fig.
Monthly counts of compound dynamical extremes (CDEs) for ERA5 during 1979–2018 over the MED.
JJA and DJF anomaly means of
We next investigate the temporal distribution of CDEs. For
During JJA, CDEs correspond to statistically significant positive SLP anomalies over the Western MED (north-western Africa) and the Anatolia–Black Sea region. These are separated by negative SLP anomalies spanning the Aegean Sea, the Levant and northern Egypt (Figs.
Histograms and cumulative distribution functions (CDFs) of anomaly means of
In DJF we observe an east–west dipole in SLP over the MED, that favours cold-air advection from northern Europe to the Balkans, parts of the Italian Peninsula and the southern and Eastern MED (Figs.
As a proxy for the variability within our composites in Fig.
We next test empirically whether the CDEs highlighted above have a systematic link to compound JJA warm–dry and DJF cold–wet events. During JJA,
In DJF, most of the
We next complement the statistical information provided by the histograms and CDFs with spatial distributions of percentage (%) match between CDEs and compound events. Put simply, for each grid point in Fig.
Percentage (%) of CDEs occurring during compound
In this paper, we analysed compound warm–dry (cold–wet) events during JJA (DJF) over the Mediterranean (MED) through the lens of dynamical systems theory. We specifically computed a measure of coupling (
During JJA, both
The findings that summertime
The analysis of DJF CDEs, matching cold–wet events, points to very different dynamics. Here, the largest anomalies in SLP,
Our findings highlight a close connection between CDEs, computed from dynamical systems coupling and compound JJA warm–dry and DJF cold–wet events over the MED. The link between CDEs and compound events likely issues from the fact that, in both cases, the data reflect anomalous (or highly coupled) conditions for the atmospheric variables being studied. It is of particular interest that
Based on our results, we learn the following: (i) the coupling between temperature and precipitation at large scales is driven by specific regions and processes (e.g. Cyprus Low), and therefore it does not always reflect the whole MED; (ii) the coupling results are sensitive even to non-extreme events, and thus the co-recurrence ratio (
The ERA5, ERA5 10-member ensemble and ERA-Interim reanalysis datasets used in this work are freely available from the European Centre for Medium-Range Weather Forecasts (ECMWF) websites
The supplement related to this article is available online at:
PDL designed the study, performed the analyses and created the figures. GM, DF and DC contributed to the methods and study design. PDL and GM wrote the first paper draft. All the authors contributed to the writing.
The authors declare that they have no conflicts of interest.
This article is part of the special issue “Understanding compound weather and climate events and related impacts (BG/ESD/HESS/NHESS inter-journal SI)”. It is not associated with a conference.
The data analysis was performed on the VU HPC BAZIS cluster. The authors would like to thank the three referees and the editor for their constructive comments, which significantly improved the paper.
This is TiPES contribution no. 15. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 820970. Paolo De Luca was also supported by an E-COST STSM (DAMOCLES, Action CA17109). Gabriele Messori was partly supported by the Swedish Research Council Vetenskapsrådet under grant agreement no. 2016-03724. Philip J. Ward was supported by a VIDI grant from the Dutch Research Council (NWO, grant no.: 016.161.324).
This paper was edited by Jakob Zscheischler and reviewed by Olivia Romppainen-Martius, Vera Melinda Galfi, and Emanuele Bevacqua.