2024/08/19 Poland Floods


August 2024 Poland floods locally exacerbated by both human-driven climate change and natural variability

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Press Summary (First Published 2024/08/20)


Event Description

On August 19th 2024, a severe storm system swept through Poland, causing extensive damage across multiple regions, mostly due to flooding. The western region of Greater Poland (Wielkopolska) and the east-central province of Mazowieckie, which includes Warsaw, were particularly hard-hit. In Warsaw’s Natolin area, warehouse roofs were severely damaged, and in the village of Chlebnia near Grodzisk Mazowiecki, the roof of a logistics centre collapsed with several people inside, though no injuries were reported. The storms also caused significant flooding in Żyrardów, located 45 kilometres west of Warsaw, and in Greater Poland, where streets and cars were submerged. The city of Ostrów Wielkopolski was especially affected, with national roads 11 and 12 inundated and numerous properties, including a Tax Office and local schools, requiring emergency water pumping. The Poland meteorological office issued a warning and reported record breaking rain amounts reaching 120mm within 24 hrs, making this the biggest rainfall event in 40 years.

The Surface Pressure Anomalies show a negative (cyclonic) anomaly, centered between Ukraine and Belarus, also affecting the eastern half of Poland. This depression was the main driver of the storms that caused the Poland floods. Temperature anomalies show positive values over the same areas affected by negative pressure anomalies, with up to 6 °C in southeastern Poland. Precipitation data show several areas of accumulation across Poland, with daily values up to about 20 mm. Wind speed data show that most of the domain was affected by moderate winds, with values around 10-15 km/h almost everywhere.

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, 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-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 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 [15°E 25°E 47°N 57°N]. The Surface Pressure Changes show that similar depressions are not deeper than in the past, while atmospheric pressure is up to 1.5 hPa lower in the present than they are in the past in the western part of the domain. The Temperature Changes show up to +2°C warmer conditions in the present than in the past. The Precipitation Changes show significant increasing precipitation in Eastern Poland experiencing up to 30% (3-5 mm/day) more precipitation in the present than in the past. Windspeed Changes indicate no significant changes. We also note that Similar Past Events occur with the same seasonality in the past and present periods. Changes in Urban Areas reveal that Warsaw, Kalisz, and Lodz are up to 4.5 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 Pacific Decadal 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 those producing Poland Floods show increasing precipitation (1-5 mm/day, namely up to 30% more precipitation) over Eastern Poland in the present compared to the past.  We interpret Poland floods as an event whose local characteristics can mostly be ascribed to human driven climate change.

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.