2023/11/01-03 Storm Ciarán


Strong winds in storm Ciarán likely influenced by both human-driven climate change and natural variability

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Press Summary (First Published 2023/11/07, Updated 2023/11/22)

Event Description

On November 1-3, 2023, Storm Ciarán, having previously impacted south-west England and northern France with heavy rain and winds gusting up to 180 kilometers per hour, reached Italy, resulting in tragic consequences including loss of life, extensive mud, and widespread flooding. Storm Ciarán exhibited an unusual fusion of heavy precipitation and high winds spanning large regions. It has been classified as a “weather bomb” since its central pressure deepened by at least 24 hectopascal (hPa) in 24 hours, reaching a near-record low pressure of 953 hPa, being the second-lowest sea level pressure observed in these regions over the last 200 years. The very quick pressure dropping in their center strengthens the winds which swirl around them and makes this type of storm even more unpredictable.

Storm Ciarán inflicted numerous injuries throughout north-west Europe, with casualties caused by falling trees, including a truck driver in northern France, two individuals in Belgium, and a hiker in Germany. Additionally, a person in the Netherlands lost their life due to a falling tree, and several others sustained injuries from flying debris. In France, 15 people, including seven firefighters, were injured by falling trees, with record-breaking winds of up to 207 km/h recorded in Brittany. The storm also necessitated evacuations, road closures, and severe weather advisories across mainland France. In Italy's Tuscany region, Storm Ciarán resulted in unprecedented rainfall, triggering floods that left residents trapped in their homes, inundated hospitals, and caused car overturns. At least two individuals were reported missing, and seven casualties have been confirmed, prompting the government to declare a national state of emergency. Tuscany experienced wind speeds of up to 150 kilometers per hour and rainfall not seen in at least half a century. Streets, residences, hospitals, factories, shopping centers, and riverbanks in areas like Prato, Pistoia, Pisa, and Campi Bisenzio were inundated. More than 20,000 people were left without power for extended periods, with 9,000 users experiencing outages in the morning and 4,600 in the evening. In some municipalities, there was also a shortage of water supply. Approximately 14,000 individuals reside in areas accessible only by amphibious vehicles. The rapid-moving front also impacted Friuli Venezia Giulia, accompanied by high-altitude southwest winds and lower-layer south winds. High water levels were observed in Trieste, Grado, Monfalcone, and Marano Lagunare, with storm surges, flooding, and fallen trees in several municipalities, along with landslides and road closures. Rainfall within an 18-hour period was generally intense, ranging from 30 to 50 millimeters, with peak levels reaching 60 to 90 millimeters in the Julian Prealps and Natisone Valleys.

The Surface Pressure Anomalies reveal a large negative (cyclonic) anomaly over Western and Central Europe. In the context of Atlantic extratropical storms, this setup has the tendency to transport moist and warm air from Western Africa to central Europe, which in turn amplifies wind strength. Windspeed data shows large areas of Europe with winds between 40 km/h and 60 km/h.

Climate and Data Background for the Analysis

The IPCC AR6 WG1 report states that climate change impacts on storminess in Europe with negative repercussions that are exacerbated by rising sea levels and heavy precipitation. Shifts in atmospheric circulation patterns are anticipated due to the unequal warming of land and ocean. This differential warming may lead to reduced continental near-surface relative humidity and contribute to localized decreases in precipitation. Climate models consistently indicate a potential increase in the frequency and intensity of severe thunderstorms characterized by tornadoes, hail, and winds.

Projections indicate that mean wind speeds are likely to decrease in Mediterranean areas and possibly in Northern Europe for global warming levels of 2°C or higher, particularly beyond the middle of the century. On the contrary, a modest increase in the frequency and intensity of extratropical cyclones, strong winds, and extratropical storms is expected for northern, central, and western Europe for the same warming levels. Changes in winter storminess are instead complex and varied. In the Euro-Atlantic region, significant changes in winter storminess are primarily expected after surpassing the 1.5°C warming threshold. These changes are influenced by shifts in the atmospheric stratification and temperature gradients at different altitudes.

Our analysis approach rests on looking for weather situations similar to those of the event of interest having been observed in the past. For storm Ciaran, 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.

ClimaMeter Analysis

We analyse here (see Methodology for more details) how events similar to Storm Ciarán 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 [-18°E 30°E 35°N 65°N]. Surface pressure changes indicate that storms resembling Ciarán exhibit pressure anomalies deeper by 3 hPa to 5 hPa in the present than in the past. Additionally, Windspeed changes suggest that these storms are now 4 km/h up to 10 km/h windier over Ireland, Scotland and the Mediterranan sea and less windy over Southern England. Precipitation changes indicate that these storms are now 6 mm/day up to 12 mm/day wetter over Mediterranean Europe. From the analysis in the urban areas we found that Pisa (Tuscany, Italy) is getting wetter in the present than in the past during storms similar to Ciarán, Cork (Ireland) is also experiencing windier conditions, while Brest (France) is not experiencing significant changes. We also note that Similar Past Events have become more common in November, while they previously occurred in October.

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.

Conclusion

Based on the above, we conclude that windstorms similar to Storm Ciarán are more intense with lower pressure (3 hPa to 5 hPa)  and stronger winds (4 km/h to 12 km/h) over Ireland and Scotland and weaker winds (3 km/h to 6 km/h) over Northern France in the present than in the past. We interpret Storm Ciarán as an unusual event for which natural climate variability played a role.

Additional Information : Complete Output of the Analysis

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.