Properties of extreme meteorological and climatological events are changing under human-caused climate change. Extreme event attribution methods seek to estimate the contribution of global warming in the probability and intensity changes of extreme events. Here we propose a procedure to estimate these quantities for the flow analogue method, which compares the observed event to similar events in the past.

This study identifies five warm-season weather regimes (WRs) to investigate the link between tornado activity and large-scale atmospheric circulations. Certain WRs strongly affect tornado activity due to their relationship with the environment. When a WR that positively affects tornado activity persists over multiple days, it further increases the tornado activity probability. The links found highlight the potential application of WRs for developing better seasonal prediction of tornadoes.

This study is an exploration of how extreme winter weather events across the Northern Hemisphere are influenced by the rare merging of the Atlantic and African jets, beyond such typical factors as the North Atlantic Oscillation (NAO) and El Niño–Southern Oscillation (ENSO). We identify unique surface signals and changes in cyclone paths associated with such persistent winter jets merging over the Atlantic, offering insights into these extreme winter weather patterns. 

This study compares the dynamical structures that characterise long-lasting (persistent) and short hot spells in Western Europe. We find differences in large-scale atmospheric flow patterns during the events and particular soil moisture evolutions, which can account for the variation in event duration. There is variability in how drivers combine in individual events. Understanding persistent heat extremes can help improve their representation in models and ultimately their prediction.

To improve decision-making in the water–energy–food nexus, we untangle the complex network of physical processes driving regional precipitation regimes in the present and near-future climates using a data-driven mechanistic approach to reduce the uncertainty in future projections. The main mechanistic link revealed is that the generalised warming of the oceans suppresses precipitation in northeastern and southeastern Brazil, explained by an intensified Hadley circulation.

The results of this study show that extreme rainfall in November 2023 over Equatorial Africa was controlled by several factors, including strong sea-surface-temperature anomalies in the Niño-3.4, North Tropical Atlantic, Equatorial Atlantic and Indian Ocean Dipole regions; changes in zonal winds; the Walker circulation; the moisture flux and its divergence; and the easterly jets. The information we derive can be used to support risk assessment in the region and to improve our resilience to ongoing climate change.

Cold fronts are often associated with areas of intense precipitation (cells) in the warm season, but the drivers and environments of cells at different locations relative to the front are not well-understood. We show that cells ahead of the surface front have the highest amount of environmental instability and moisture. Also, low-level lifting is maximised ahead of the surface front and upper-level lifting is particularly important for cell initiation behind the front. 

The jet stream is the main feature of upper-level flow and drives the weather at the surface. It is stronger and better defined in winter and has mostly been studied in that season. However, it is very important for (extreme) weather in summer. In this work, we improve and use two existing and complementary methods to study the jet stream(s) in the Euro-Atlantic sector, with a focus on summer. We find that our methods can verify each other and agree on interesting signals and trends.

We study the impacts of globally increasing sea surface temperatures and sea ice loss on the atmosphere in wintertime. In future climates, the jet stream shifts southward over the North Atlantic and extends further over Europe. Increasing sea surface temperatures drives these changes. The region of high activity of low-pressure systems is projected to move east towards Europe. Future increasing sea surface temperatures and sea ice loss contribute with similar magnitude to the eastward shift.

We studied severe hailstorms that occurred in Switzerland on 28 June 2021 using a weather prediction model to understand how they evolved. We found that the storms moved toward areas with more storm energy. Hailfall was quickly followed by heavy rain. Just before the storms died out, the air feeding them stopped coming from near the ground. We also observed a delay between different types of precipitation forming in the incoming air. 

This study explores how sea surface energy influences both the atmosphere and ocean at various vertical levels during extreme Mediterranean cyclones. It focuses on cyclones' precipitation and wind speed response, as well as on ocean temperature variation. The findings highlight the regional coupled model's ability to coherently represent the thermodynamic and dynamic processes of the cyclones across both the atmosphere and the ocean.

This work presents the identification of Saharan warm-air intrusions in the western Mediterranean, which are the displacement of air masses formed over the Sahara toward the west of the Mediterranean region. We focus on the recent past and obtain a catalogue of intrusion days. The results show the existence of different types of intrusions, important impacts on extremely high temperatures in the Mediterranean and Europe, and the dynamic mechanisms that can cause the onset of these events.

The impact of Arctic sea ice loss on the North Atlantic jet stream is debated, with some linking changes to ice loss and others to natural variability. This study uses a new method to explore how future sea ice loss will affect the jet stream. In half of the models, the jet shifts equatorward, but its speed and tilt are unchanged. Some models also exhibit more jet splitting. The results suggest that future sea ice loss is unlikely to significantly weaken the jet stream or make it more variable.

Our work compares different machine learning approaches for creating long-term classifications of daily atmospheric circulation patterns using input data from surface meteorological observations. Our comparison reveals that a feedforward neural network performs best at this task. Using this model, we present a daily reconstruction of a commonly used weather type classification for central Europe that dates back to 1728.

Mid-latitude atmospheric jet streams sometimes create "waveguides", which are thought to increase the chance of quasi-stationary waves – atmospheric circulation patterns that can lead to extreme weather events. We compare two methods of identifying atmospheric waveguides, finding that one method seems to be less impacted by the presence of waves and provides much stronger correlations with enhanced quasi-stationary waves, and recommend this method for future studies.