2023/08/27-29 Mediterranean Depression Rea
Heavy precipitation in Mediterranean Depression Rea influenced by both human-driven climate change and natural variability
Mediterranean depressions similar to Rea are between 2 and 6 mm/day drier in Piedmont and Liguria and 2 and 6 mm/day wetter in Friuli and Veneto in the present than they have been in the past.
On August 27th, a trough extending from Scandinavia to the Iberian Peninsula entered the Mediterranean region from the west, ending the exceptional heatwave that affected southern Europe in the two previous weeks. The trough prompted the formation of a Mediterranean cyclone, named depression Rea, which formed during the day of August 27th and reached the Gulf of Genoa on the following day, igniting several convective systems. The first complex of thunderstorms hit Palma de Mallorca, in the Balearic Islands, around 10 am, and reached Sardinia in the evening. Other thunderstorms and squall lines fired to the north and west of this convective system, some of which hit Corsica, producing severe wind gusts. At night, a stationary v-shaped storm formed south of Genoa, causing flooding, and eventually merged with the previously existing storms as the cyclone progressed towards the east. On the 28th the depression strengthened in the gulf of Genova as a Lee cyclone and this created a strong south westerly flow to the east of the cyclone advecting moist air to the northernmost part of the Adriatic sea. This triggered severe convective storms in the north eastern Italian regions causing several landslide, with floods in Venice and Trieste resulting in the wettest summer season on record (since 1994).
This strong thunderstorm episode was characterized by overall negative Surface Pressure Anomalies with respect to the climatology, and heavy Precipitation, in particular over the Balearic Islands, Genova, the northern Italian regions. Depression Rea reached the Mediterranean sea in a context of very high sea surface temperatures, with widespread extreme positive anomalies even compared to the existing positive trend, which contributed to the onset of an unstable environment characterized by large values of convective available potential energy.
In Chapter 11 of the IPCC AR6 report it is stressed that: "because the definition of severe convective storms varies depending on the literature and the region, it is not straightforward to make a synthesizing view of observed trends in severe convective storms in different regions. In particular, observational trends in tornadoes, hail, and lightning associated with severe convective storms are not robustly detected due to insufficient coverage of the long-term observations". Because of these limitations, no statement about changes in convective storms in the Mediterranean region are made. Moreover, in Chapter 12, no statement on past trends in extreme precipitation is made for the Mediterranean area, but it is mentioned that: "Significant negative trends of cyclone frequency in spring and positive trends in summer have been found in the Mediterranean basin for the period 1979–2008", coherently with our results (see below). Finally, the IPCC AR6 report remarks that: "The mean SST of the Atlantic Ocean and the Mediterranean has increased between 0.25°C and 1°C since 1982–1998. This mean ocean surface warming is correlated to longer and more frequent marine heatwaves in the region". The high sea-surface temperatures provide "fuel" for strong convective events. Overall, convective events are characterized by high uncertainty and large natural variability, so that no clear statements about past trends are available for the Mediterranean region. However, it is possible to detect a shift towards the summer of Mediterranean cyclones and the co-occurrence of warmer sea surface temperatures and more frequent marine heatwaves.
Our analysis approach rests on looking for weather situations similar to those of the event of interest having been observed in the past. For Rea, we have medium-high confidence in the robustness of our approach given the available climate data, as the event is similar to other past events in the data record. However, we understand a possible role of the Mediterranean sea surface temperature trend, which is not included in this analysis.
We analyse here (see Methodology for more details) how events similar to Rea have changed in the present (2001–2022) compared to what they would have looked like if they had occurred in the past (1979–2000) in the region [-2°E 27°E 34°N 49°N]. Surface Pressure Changes show small differences in the western Mediterranean sea, suggesting that climate change has not affected the dynamics of this type of event. Precipitation Changes show that similar events result in lower precipitation in Piedmont and Liguria (ranging from 1 to 6 mm/day), higher precipitation in Veneto and Friuli (ranging from 2 to 8 mm/day). For the urban areas, we observe a decrease in precipitation in Genoa and an increase of 3 mm/day in Trieste and Venice within the Veneto and Friuli region. The general increase in precipitation is compatible with a thermodynamic contribution provided by the increasingly warmer Mediterranean Sea, which provides ample potential energy to fuel convective systems over the region. Despite the fact that surface temperature in the Mediterranean region is now 1.5 °C warmer than pre-industrial levels, temperatures associated with events like Rea do not differ significantly in the main cities affected by the storms. We also find that Similar Past Events have become more frequent in August, while they previously occurred chiefly in June, July and September. Previously, no Similar Past Events occurred in August.
Finally, we find that sources of natural climate variability, notably the Atlantic Multidecadal Oscillation and the Pacific Decadal Oscillation, may have influenced the event. This suggests that the changes we see in the event compared to the past may be partly due to human driven climate change, with a contribution from natural variability.
Based on the above, we conclude that Mediterranean depressions similar to Rea show lower atmospheric pressure and are between 2 and 6 mm/day drier in Piedmont and Liguria and 2 and 6 mm/day wetter in Friuli and Veneto in the present than they have been in the past. We interpret depression Rea as an event whose characteristics can mostly be ascribed to human driven climate change.
Flavio Pons, IPSL-CNRS, France 📨email@example.com 🗣️French, Italian, English
Erika Coppola, ICTP, Italy 📨firstname.lastname@example.org 🗣️ Italian, English
Additional Information : Complete Output of the Analysis
NB1: The following output is specifically intended for researchers and contain details that are fully understandable only by reading the methodology described in Faranda, D., Bourdin, S., Ginesta, M., Krouma, M., Noyelle, R., Pons, F., Yiou, P., and Messori, G.: A climate-change attribution retrospective of some impactful weather extremes of 2021, Weather Clim. Dynam., 3, 1311–1340, https://doi.org/10.5194/wcd-3-1311-2022, 2022.
NB2: Colorscales may vary from the ClimaMeter figure presented above.
The figure shows the average of surface pressure anomaly (msl) (a), average 2-meter temperatures anomalies (t2m) (e), cumulated total precipitation (tp) (i), and average wind-speed (wspd) in the period of the event. Average of the surface pressure analogs found in the counterfactual [1979-2000] (b) and factual periods [2001-2022] (c), along with corresponding 2-meter temperatures (f, g), cumulated precipitation (j, k), and wind speed (n, o). Changes between present and past analogues are presented for surface pressure ∆slp (d), 2 meter temperatures ∆t2m (h), total precipitation ∆tp (i), and windspeed ∆wspd (p): color-filled areas indicate significant anomalies with respect to the bootstrap procedure. Violin plots for past (blue) and present (orange) periods for Quality Q analogs (q), Predictability Index D (r), Persistence Index Θ (s), and distribution of analogs in each month (t). Violin plots for past (blue) and present (orange) periods for ENSO (u), AMO (v) and PDO (w). Number of the Analogues occurring in each subperiod (blue) and linear trend (black). Values for the peak day of the extreme event are marked by a blue dot. Horizontal bars in panels (q,r,s,u,v,w) correspond to the mean (black) and median (red) of the distributions.