2023/07/05 Storm Poly in Central Europe

Strong winds in storm Poly mostly strengthened by human-driven climate change

Press Summary (First published 2023/08/23, last updated 2023/11/22)

Event Description

On July 5th 2023, a summer extratropical storm named Poly hit Germany, the Netherlands and Denmark, causing significant damage and resulting in 2 casualties. It featured hurricane-force wind gusts locally up to 146 km/h, the strongest ever recorded for a summer storm in the Netherlands. The storm's rapid cyclogenesis began over the North Atlantic, and its development was tracked through satellite imagery. Unusually powerful for July, the storm's impact was seen across Germany, the Netherlands and Denmark. The severe winds were accompanied by heavy rainfall and led to various damages, including uprooted trees and transportation disruptions. The majority of severe weather reports associated with the storm concerned intense wind events.

Storm Poly displayed clear negative Surface Pressure Anomalies over the Netherlands, Denmark and parts of North-Western Germany, while Windspeed during the storm was above 30 or 40 km/h over a large swath of the Baltic and Northern Europe

Climate and Data Background for the Analysis

In Chapter 11 of the IPCC AR6 report, it is highlighted that there is low confidence in recent total extratropical storm changes globally, but medium confidence in a poleward storm track shift since the 1980s. Understanding past-century extratropical storm trends is hindered by interannual variability and assimilation data variations in reanalyses, particularly for the pre-satellite era. Agreement is better for stronger cyclones in reanalyses and tracking algorithms. Data for the Northern Hemisphere supports a decreased central pressure for cyclones (<970 hPa) in summer and winter during 1979–2010, but with non-monotonic trends. The background mean sea level pressure's seasonal and regional variations complicate assessing extratropical storm dynamical intensity trends based on absolute central pressure.

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

ClimaMeter Analysis

We analyse here (see Methodology for more details) how events similar to storm Poly 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 [0°E 25°E 46°N 60°N]. The Surface Pressure Changes show that the pressure over the storm area has become lower, favouring more intense cyclones in the present than in the past. Windspeed Changes show that similar events produce winds which are between 2 and 6 km/h stronger than what they would have been in the past, consistent with the Surface Pressure Changes. Storms similar to Poly are associated with stronger winds in Hamburg (Germany) and Copenhagen (Denmark) than they would have been in the past. We also note that Similar Past Events have become more common in the month of August, while they previously occurred more in other summer months (peaking in July) or even in September.

Finally, we find that sources of natural climate variability, notably the Pacific Decadal Oscillation, may have partly influenced the event. This means that the changes we see in the event compared to the past may be due to human driven climate change.


Based on the above, we conclude that storms similar to Poly display lower pressures and stronger winds in the present than in the past.  We interpret this storm as a largely unique event whose characteristics can mostly be ascribed to human driven climate change.

Contact Author

Davide Faranda, IPSL-CNRS, France  📨davide.faranda@lsce.ipsl.fr  🗣️French, Italian, 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.