The influence of soil moisture on the extreme precipitation event in July 2021 in Western Europe – A storyline approach

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 event? We are investigating this question using the example of heavy precipitation in July 2021, which led to destructive flash floods in Western Europe.

To quantify the importance of land-atmosphere coupling and continental moisture sources for the precipitation, we perform numerical simulations with different levels of soil moisture. In one set of simulations, we prescribe the initial conditions only, in another set of simulations, we constantly force the soil moisture to specific values. In this way, we can distinguish between the effect of water availability at the surface and the role of the land-atmosphere coupling. Furthermore, we add moisture tracking to our analysis to see if the modifications also impact the spatial distribution of moisture source regions.

Ensembles of simulations are performed using a global set-up of the ICON numerical weather prediction model. This allows the system to evolve without prescribed lateral boundary conditions. However, the predictability of the event then depends exclusively on the initial conditions. In order for ICON to predict the extreme event, an initial state close in time to the event is required. However, this time may be too short for the moisture changes to take effect. For this reason, we are developing a modified simulation set-up, which uses data assimilation to constrain the evolution of the system into an extreme just enough so that our modifications to the soil are not undone.

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 a reference of the changes we can expect as a result of human influence.