Project: Quantifying controls on the intensity, variability and impacts of extreme European STORMS
by Clément Bouvier and Victoria Sinclair (University of Helsinki)

Throughout the year, low-pressure systems regularly move across Europe, usually from west to east, bringing cloud, rain and windy weather. Sometimes these weather systems can become very intense, and the winds and rain associated with them can cause damage to buildings and infrastructure, flooding, and can disrupt electricity supply and travel. Although the short-term weather forecasts of these storms are now quite accurate, it still remains uncertain how these storms, and their impacts, are likely to change in the future as our climate changes. Some of this uncertainty is because our understanding of what controls the strength and impacts of these storms is incomplete.

The aim of this project is to understand what controls the strength and structure of these low-pressure systems. We will quantify how the atmospheric state that the low-pressure systems develop in affects the strength and structure of these low-pressure systems. This atmospheric state can be described by various parameters, for example, the mean temperature, moisture content, and upper-level wind speeds (i.e. the strength and width of the jet stream). Since there are lots of different parameters we want to study (not just the ones described above), we want to do lots of experiments in a high controlled manner. Therefore, we will run a large ensemble of simulations of idealised low-pressure systems using the numerical weather prediction model OpenIFS. Although the simulations are idealised, the weather systems that develop look very like real weather systems that we observed in reality. Each ensemble member differs in its initial atmospheric state, and we choose these initial states to cover everything from the current climate to past pre-industrial climates to the most extreme future climate projections. This is exciting because although idealised simulations of low-pressure systems have been performed before, this is the first time that such an extensive exploration of the parameter space will be conducted.

Once we have the results from the large ensemble, we will calculate different measures of the strength of the storms and then use machine learning techniques to see how these relate to the initial states. Our results will hopefully increase in confidence in how these storms and their impacts will change in the future.

Technical information:
Run time: between 8 and 9 hours for 1 workunit (1 core, Xeon Gold 6230)
Number of files: 480 files
Maximum size of individual files: 1.3MB for 2D fields output files, 13.3MB for spectral output files, 7.1MB for 3D fields output files
Total disk load: 2.0GB