2024/09/13-15 Storm Boris


Heavy Precipitations in Storm Boris exacerbated by both human-driven climate change and natural variability

Press Summary (First Published 2024/09/16, Updated 2024/09/17)


Storm Boris brought torrential rainfall and severe flooding across Central and Eastern Europe, affecting Romania, Poland, Austria, Slovakia, and the Czech Republic. The storm, fueled by a sharp contrast between polar air and warm, moist air from the unusually hot Mediterranean, dumped extraordinary amounts of rain, with some areas in Lower Austria receiving between 300 and 350 mm over just a few days—two to four times the average for September. In other parts of Austria, rainfall totals reached 270 mm, while in the mountains, even at lower elevations, heavy snowfall occurred, with Obertauern recording one meter of snow. This excessive rainfall caused rivers like the Elbe, Oder, Morava, and Salzach to overflow, leading to widespread flooding. In Poland, the southern regions of Silesia and Lower Silesia were particularly hard-hit. In Stronie Śląskie, a dam failure on the Biala Ladeckia River unleashed a destructive wave on the town of Kłodzko, and in Glucholazy, two bridges were washed away. In total, eight people lost their lives—six in Romania, one in Poland, and a firefighter in Austria—while four others remain missing in the Czech Republic. Widespread power outages and significant disruptions to transport systems occurred, with rail traffic suspended between Poland and the Czech Republic and parts of Vienna’s metro system closed. Despite efforts to mitigate the human toll, ongoing evacuations continue as new rains are expected. In Romania, storm Boris caused severe flooding, particularly in the eastern regions of Galati and Vaslui counties (eastern Romania). Certain areas in Galați county received more than 150 litres of rainfall per square meter, three times more than the climatological average for a month of September. Around 5,000 households were severely affected. The full extent of the damage is comparable if not larger than the catastrophic floods of 1997 and 2013 in Central Europe. 

The Surface Pressure Anomalies show a large depression system (up to -10 hPa surface pressure anomalies) at the core of storm Boris centred over Eastern Europe. This depression was the main driver of the massive floods. Temperature anomalies show  negative anomalies (up to -10 °C) over the same areas affected by negative pressure anomalies. The contrast between the cold air and the warmer than average sea surface temperatures of the Mediterranean and the Black sea determined the extreme precipitation. Indeed, Precipitation data show several areas of accumulation across Eastern Europe, with daily values up to 100 mm. Windspeed data show that most of the domain was affected by moderate to high winds, with values peaking around 100 km/h in some areas.

Climate and Data Background for the Analysis

The IPCC AR6 WGI report states that the water cycle variability and extremes are projected to increase faster than the average change and in most of the tropical and extratropical regions. In the extratropics during the warmer season, interannual variability of precipitation and runoff are increasing faster than the seasonal changes (Chapter 8). 

At the more local scale, according to Chapter 12  there is high confidence of observed increasing trend of river floods in Western and Central Europe (including Romania, Poland, Austria, Slovakia, and the Czech Republic), and this increase will continue with high confidence for global warming levels higher than 1.5 °C.   This is well highlighted in panels (a) and (c) of Figure 12.9, that show positive changes of the 1-in-100-year river discharge affecting most of west and central Europe. This suggests an increment in intensity of extreme rainfall events that overload the small river catchments, ultimately increasing the risk of flooding.

Our analysis approach rests on looking for weather situations similar to those of the event of interest having been observed in the past. For this event, we have  medium-low confidence in the robustness of our approach given the available climate data, as the event is unusual in the data record.


ClimaMeter Analysis

We analyze here (see Methodology for more details) how events similar to the low pressure system leading to the Poland Floods 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 [3°E 30°E 42°N 55°N]. Surface Pressure Changes show that similar depressions are deeper than in the past, with atmospheric pressure up to 2 hPa lower in the present than they are in the past in the eastern part of the domain, strictly corresponding to the core of the low-pressure system. Temperature Changes show up to -2 °C colder conditions in the present than in the past over Vienna and the closest region. Precipitation Changes show significant increasing precipitation in the area affected by the storm experiencing up to 20% (4-8 mm/day) more precipitation in the present than in the past.  Some limited areas of Bosnia, less affected by the floods experience a decrease in precipitation.  Windspeed Changes indicate significant changes on a limited area far from the core of the storm. We also note that Similar Past Events occur with similar seasonality in the past and present periods, although with a slight increase in October in the present climate. Changes in Urban Areas reveal that Vienna and Krakow are up to 10 mm/day wetter (up to  15% more precipitation) in the present compared to the past. 

Finally, we find that sources of natural climate variability, notably the Atlantic Multidecadal Oscillation may have influenced the changes in this event. This suggests that the changes we see in the event compared to the past may be due to human driven climate change, with a  minor contribution from natural variability.

Conclusion

Based on the above, we conclude that depressions similar to Storm Boris producing Central Europe Floods show deeper pressure minima (-2 hPa) and increasing precipitation (4-8 mm/day, namely up to 20% more precipitation) over Eastern Austria, Czech Republic and Southern Poland in the present compared to the past.  Some limited areas of Bosnia, less affected by the floods experience a decrease in precipitation.  We interpret Storm Boris as an exceptional event in terms of precipitation and a very uncommon event in terms of pressure pattern whose characteristics can mostly be ascribed to human driven climate change.

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 📨coppolae@ictp.it 🗣️Italian, English

-Bogdan Antonescu, Bucharest University,  📨bogdan.antonescu@g.unibuc.ro 🗣️Romanian,  English

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.