In PERSEVERE we aim at improving our physical understanding of atmospheric wave-resonance events in summer. Such events are often associated with persistent summer extremes in Europe, such as heatwaves, droughts and storms that bear important environmental and societal risks. For instance, in 2018, Western Europe experienced a record long hot-dry period lasting essentially the full summer causing massive impacts on agricultural production. There is evidence that weather persistence has indeed increased in Europe over the last decades, associated with changes in atmosphere dynamics, but the uncertainties are large and the exact drivers not well understood. Here, with the use of Machine Learning methods in combination with climate models, we will assess how hemispheric-scale jet regimes are connected to wave-resonance events, we will extract causal precursors, and we will derive emergent constraints in order to reduce uncertainty in future model projections. This project aims at answering the questions:
i) How often do double-jet regimes and or/blocking situations coincide with each other and with wave-resonance events?
ii) How do such atmospheric configurations affect extreme weather in central Europe?
iii) Are there trends in the occurrence of double-jet, blocking, and wave-resonance events? iv) What are the causal drivers (e.g. Arctic Amplification, early-season snowmelt) of wave-resonance events in observations and models?
v) How well do models simulate such events and can we improve model simulations with emergent constraints derived from causal relationships?
