Has world warming made the heavy rainfall in Central Europe in September 2024 extra possible? – Are you completed with that?
Of climate etc.
by Frank Bosse
Neither the trend analysis nor the model-observation comparison support the conclusions of the attribution study, which found the following:
“The combined change attributable to human-caused climate change represents approximately a doubling in probability and a 7% increase in intensity.”
Beginning on September 11, heavy rains occurred in parts of Austria, Poland and the Czech Republic. Initial estimates indicate record high levels of precipitation over a wide area as a result of a “Vb weather situation”, named after the historical classification of the paths of low pressure areas in Europe. In Vb weather conditions, a low pressure area extends to the Mediterranean, from there to the northeast and usually ends in the Baltic region of Europe. A Vb condition is very often associated with a lot of rain in Central and Eastern Europe and flood events such as 1997 (Oder) and 2002 (Elbe).
However, an “attribution study” appeared just a few days later. The core message of the event (quoted in the media) was:
“The combined change attributable to human-caused climate change represents approximately a doubling in probability and a 7% increase in intensity.”
To assess the robustness of the claim, the full text of the attribution study was downloaded.
The meteorological classification of the event in question includes several features of atmospheric dynamics. The triggering event was an “Arctic eruption,” which also involved an extreme northward shift of the Intertropical Convergence Zone (ITCZ). To make matters worse, there was a stable blocking high pressure field to the north of the area in question, so the area of precipitation was relatively stationary and could not move northwards towards the Baltic Sea as usual.
The crucial question is whether the thermodynamic element (related to warming due to “climate change”) contributing to the events described can actually be quantified with any degree of robustness, as claimed in the attribution study.
The attribution study describes trend analyzes of observation data (E-Obs.) and (weather) model observation reanalysis data (ERA5) for the period 1950-2023 (2024). The data used is available via the “KNMI Climate Explorer” and enables the numbers to be evaluated. The study uses the GMST-GISS dataset to describe the connection of heavy rainfall in Central Europe to a warmer world. The attribution study states:
“All datasets show similar trends across the region, with increasing trends…” (see Section 3.1)
The same data set is used here, but averaged over the relevant European area and not globally. The mean temperature anomaly 1950-2023 in the region 20°W-25°E; 35°N-65°N is shown below. This region includes more land (warming faster than the ocean) than the global median land share of about 30%.
Fig.1: The temperature time series (GISS) in Europe. The figure was created using the KNMI Climate Explorer.
The (not too surprising) observation: from 1950 to around 1981, temperatures showed no increase. The anthropogenic warming manifested in average temperatures began around 1981, not 1950.
To calculate trends in “RX4days” precipitation (that is, the accumulation of 4 days of precipitation), the data for ERA5 for 1950-2024 was recalculated:
Fig.2: The outstanding event in September 2024 can be clearly seen. This means that the trend curve for 1981-2024 (green) is positive (a “one-year trend”), and for 1981-2023 (black) it is zero. The figure was generated using ChatGPT.
The Ordinary Least Square (OLS) trend 1950-2024 (blue) is robustly positive (p=0.025), according to the attribution study. However, it was not mentioned that the trend after the late 1960s would have become insignificant if calculated up to 2024. If the increasing trend from 1950 to 2024 was due to “man-made climate change” after 1981, one would NOT expect the increasing trend in 2024 to be completely insignificant (p=0.32) and for 1981-2023 to be (black). it zero. Given these findings, OLS trends through 2024 may be more due to internal variability. In the period 1950–1981 without warming (see Fig. 1), the most positive trend slope (orange) of RX4day was twice as steep as in the period 1981–2024 when the forced warming was observed.
The study evaluates the climate models used for attribution analysis. Many models belong to the CMIP6 family. These models are known to have significant difficulties in understanding atmospheric dynamics due to their low resolution. The multi-model average shows no competence in the spatial correlation between model and observation (E-Obs.) for precipitation in the study area (46°N-52°N; 11°E-24°E).
Fig.3: The spatial correlation between the CMIP6 multi-model average precipitation and the observations (E-Obs.) for the warm seasons 1975-2023. The figure was created using the KNMI Climate Explorer.
A meaningful correlation should be a prerequisite for attributing anthropogenic warming, as simulated in the CMIP6 models, to a clear extreme precipitation event based on model comparisons with the real world.
In Table 4.1 of the attribution study, the models were evaluated, some (only a few) were rated as “good” in terms of precipitation. The model “IPSL-CM6A-LR” was rated as “reasonable”. The 1950-2023 spatial correlation to E-OBS observations during months in which Vb events were observed is shown below, also for the “good” model “EC Earth 3”, both at under 20%, not from random noise to distinguish:
Fig. 4: There is no skill in selected models of the study (white for zero correlation). The figure was created using the KNMI Climate Explorer.
Neither “IPSL-CM6A-LR” (left) nor the “EC Earth3” (right), which is labeled “good” in the study, have any capabilities when it comes to spatially correlating precipitation with the real world. This also applies to the MPI-ESM1-2LR model (“reasonable” in Table 4.1 of the study), which, however, is not shown here.
Ultimately, it seems doubtful to attribute an extreme precipitation event to climate change using the CMIP6 models. Warming oceans are certainly a source of more evaporation and also more rain, although the proportional increase in precipitation with warming is only a fraction of the increase in evaporation.
However, the influence of atmospheric dynamics is overwhelming and makes it difficult to attribute individual extreme weather events based on thermodynamic arguments.
Diploma
Upon closer inspection, neither the trend analysis nor the model-observation comparison support the conclusions of the attribution study.
The problem of unreliable studies attributing extreme weather events is not limited to extreme precipitation. As this recent article by Roger Pielke Jr. explains, attribution studies for all types of extreme weather events are generally highly dubious and appear to be conducted for “political” rather than scientific reasons.
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