2024/03/09 Storm Monica
Storm Monica intensified by both human-driven climate change and natural variability
Contact Authors
Davide Faranda, IPSL-CNRS, France 📨davide.faranda@lsce.ipsl.fr 🗣️French, Italian, English
Tommaso Alberti, INGV, Italy 📨tommaso.alberti@ingv.it 🗣️Italian, English
Erika Coppola, ICTP, Italy 📨coppolae@ictp.it 🗣️Italian, English
Flavio Pons, IPSL, Italy 📨flavio.pons@lsce.ipsl.fr 🗣️Italian, English, French
Citation
Faranda, D., Alberti, T., Coppola, E., & Pons, F. M. E. (2024). Storm Monica intensified by both human-driven Climate Change and Natural Variability. ClimaMeter, Institut Pierre Simon Laplace, CNRS. https://doi.org/10.5281/zenodo.14163643
Press Summary (First published 2024/03/11)
Storms similar to Monica are 3 hPa to 5 hPa deeper over Italy, 5-10 km/h windier over the Western Atlantic and the Western Mediterranean, and 6-13 mm/day wetter over Northern Italy in the present than they were in the past.
This was a somewhat uncommon event.
Human driven climate change and natural climate variability both played a role in driving the pressure pattern and the associated increase in precipitation/wind linked to storm Monica.
Event Description
Storm Monica hit France, Spain and Italy on March 9, 2024 leading to significant rainfall accumulations. Météo-France reported that rainfall ranged between 100 and 150 mm in 24h, with measurements reaching up to 224 mm in Ardèche and 330 mm over 48 hours in La Souche. Additionally, accumulations in the Var region varied between 60 and 80 mm, with Méounes-lès-Montrieux recording 150 mm. Wind Gusts observations reported over France reached 130 km/h and Ardeche and the Alps were also hit by severe snow storms. In France, the aftermath of the storm has led to rescue efforts, particularly in Ardèche and Gard, where four people died and four remain missing due to incidents associated with the severe weather conditions. In addition, approximately 17,000 households were left without electricity in Auvergne-Rhône-Alpes and Provence-Alpes-Côte-d'Azur, with significant power outages reported in Drôme, Ardèche, Rhône, and other departments of France.
Storm Monica has also caused serious disruptions and inconveniences in Italy, especially Liguria, Piedmont, and Valle d'Aosta, facing the brunt of the storm. All over the Alpine chain the alert was high for avalanche risk. In the Ligurian Alps, a skier died in an avalanche, part of a group of six. Four others were caught in the avalanche, with one man critically injured and airlifted to Pietra Ligure Hospital. Two women were also injured but not critically, and airlifted to Mondovì Hospital, while one man escaped unharmed. Six other skiers are missing in the Swiss Alps.. In Liguria, Piedmont, and Valle d'Aosta, landslides and heavy rain have caused road closures and isolated communities. In Piedmont, precautions have been taken against avalanches, with several roads closed, including one leading to Ceresole Reale. Lombardy is also affected, with fire department interventions and structural damage reported in Brescia and Milan. Venice activated the MoSE flood barriers, while Rome, Bari, and Naples experienced rainfall and damaging winds, which also disrupted ferry services to the islands in the Gulf of Naples. The weather situation remains critical, with ongoing alerts and updates from the Civil Protection Department. Regional authorities are coordinating response efforts.
The Surface Pressure Anomalies show a large negative (cyclonic) anomaly over Western Europe. This configuration, typical of Atlantic extratropical storms, is associated with strong southerly winds, advecting wet and warm air from Western Africa to central Europe. Temperature data show warm anomalies over a large part of the European domain (Italy, Germany, UK, and Scandinavian regions), while negative anomalies are observed over Spain, Portugal, and Western France. Precipitation Data show high daily amounts of precipitation over Spain, Portugal, South of France, the Alps and the Thyrrenian coasts. Windspeed data show large areas of the Eastern Atlantic affected by wind exceeding 50 km/h, locally peaking up to 100 km/h.
Climate and Data Background for the Analysis
In France, the event under analysis can be aptly classified as an Épisode Cévenol, named after the mountain range Cévennes situated in Southern France. These occurrences are characterized by the accumulation of cloud masses originating from the Gulf of Lion, typically accompanied by very humid south to southeast winds. Initially, these atmospheric conditions trigger orographic rainfall in the mountains, which subsequently spreads to the plains. A typical Cévennes episode unfolds over several days, yielding rainfall amounts ranging between 200 and 400 mm, occasionally reaching precipitation totals up to 600 or 700 mm in particularly severe instances.
In the IPCC AR6 report, Chapter 11 underscores the challenge of assessing climate trends and their link to intense rainfall events. The variability in rain amount definitions and limitations of long-term observations pose obstacles to drawing precise conclusions, especially concerning thunderstorms leading to flooding in Mediterranean coastal regions. Similarly, Chapter 12 refrains from making explicit statements about historical trends in extreme precipitation specific to the Mediterranean, but it still assigns medium confidence to a future increase of extreme precipitation. However, within the unique context of the Cévennes region, Ribes et al.'s research reveals a significant +22% increase in extreme rainfall intensity from 1961 to 2015, suggesting a potential influence of human-induced climate factors. Drobinsky et al. contribute by demonstrating a consistent association between temperature and extreme precipitation across the Mediterranean, noting a shift in this correlation at around 20°C. FInally, Vautard et al. 's findings highlight the heightened intensity of daily precipitation in the Cévennes mountains. Their research suggests that the likelihood of experiencing precipitation levels comparable to those observed in 2014 has likely tripled since 1950, albeit with significant uncertainties. Collectively, these studies, along with the IPCC AR6 report, shed light on evolving climate trends and their implications for extreme weather events. They provide insights into the intensification of extreme precipitation in the Cévennes region and the broader Mediterranean context, despite the complexities inherent in such assessments.
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 Monica we have high confidence in the robustness of our approach given the available climate data, as the event is very similar to other past events in the data record.
ClimaMeter Analysis
We analyze here (see Methodology for more details) how events similar to the pressure system leading to Storm Monica changed in the present (2001–2023) compared to what they would have looked like if they had occurred in the past (1979–2001) in the region [22°W 18°E 30°N 55°N]. The Surface Pressure Changes show that similar events to Storm Monica are up to 5 hPa deeper in the present climate than what they would have been in the past. The Temperature Changes show that similar events produce temperatures in the present climate that are between 2 ºC and 3 ºC warmer than what they would have been in the past, over a large area of the region analyzed. The Precipitation Changes show wetter conditions (up to 13 mm/day) over the Tyrrenhian coasts and North-East Italy, resulting in MoSE barriers activations in Venice to face Acqua Alta. Windspeed Changes indicate up to 5-10 km/h windier conditions over Western France Atlantic coasts and Western Mediterranean compared to the past. We also note that Similar Past Events previously mainly occurred in March and April, while in the present climate they are mostly occurring in February and March. Changes in Urban Areas reveal that Cevennes, Nimer, and Genoa are 3 km/h to 5 km/h less windy in the present compared to the past. Additionally, Genoa experiences up to 10 mm/day more rainfall in the present than in the past.
Finally, we find that sources of natural climate variability, notably the Pacific Decadal Oscillation and the Atlantic Multidecadal 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 storms similar to Monica are 3 hPa to 5 hPa deeper over Italy, 5 km/h to 10 km/h windier over the Western Atlantic and the Western Mediterranean, and 6-13 mm/day wetter over Northern Italy in the present than they would have been in the past. We interpret Storm Monica as an unusual event for which both human driven climate change and natural climate variability played a role.
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.