The influence of soil moisture on the extreme precipitation event in July 2021 in Western Europe

Soil moisture-precipitation feedback is an important factor in the water and energy cycles, but how important is it on the time scale of an atmospheric extreme precipitation event? We are investigating this question using the example of heavy precipitation in July 2021, which led to destructive flash floods in Western Europe.

We quantify the importance of soil moisture by running a storyline simulation. We compare the precipitation simulated in the ICON-DREAM reanalysis and in our control run to counterfactual scenarios with soils dried out to plant wilting point and soils wetted to saturation. We find that saturating the soil increases precipitation by about 10% while drying the soil decreases precipitation by about 36% comparing ensemble median values.

Moisture tracking shows that one reason is that land surfaces in the vicinity of the impacted region are relevant for fueling the heavy precipitation. We find that evaporation is not limited by water availability, which explains the non-linear response in the precipitation amounts. 

The changes in evaporation also affect the synoptic scale evolution of the event, which amplify the precipitation decrease in the dry scenario. Constraining the evolution of the event enough to produce the extreme of July 2021 was a major challenge of this study. The limited predictability of free forecasts conflicts with the need for enough lead time to allow soil moisture to impact the atmosphere in a meaningful way. We solve this problem by using data assimilation to constrain the large scale circulation of our global ICON simulations while disabling the assimilation within our region of interest.

Our work is part of the German Research Foundation (DFG) Collaborative Research Center 1502 DETECT. In DETECT we aim to answer the question of whether regional changes in land and water use impact the onset and evolution of extreme events. Our coarse approach to changes in water availability gives us an upper bound on changes we can expect as a result of human influence.