Storm Daniel (2023) is one of the most catastrophic storms ever documented in the Mediterranean. Our results highlight the different dynamics and therefore the different predictability skill of precipitation, its extremes and impacts that have been produced in Greece and Libya, the two most affected countries. Our approach concerns an analysis of the storm by articulating dynamics, weather prediction, hydrological and oceanographic implications, climate extremes, and attribution theory.

Tracking tropical cyclones (TCs) remains a matter of interest for investigating observed and simulated tropical cyclones. In this study, Random Forest (RF), a machine learning approach, is considered to track TCs. RF associates the TC occurrence or absence with different atmospheric configurations. Compared to trackers found in the literature, it shows similar performance for tracking TCs, better control over false alarms, more flexibility, and reveals key variables for TCs' detection.

Extreme weather events pose increasing challenges for aviation, including flight disruptions and infrastructure damage. This study examines the influence of anthropogenic climate change on four recent major storms across Europe, the USA, and East Asia. Our research underscores the growing intensity of extreme storms, driven by human-induced climate change, stressing the need to adapt aviation strategies to an increasingly hazardous environment.

Cold spells affect healthcare and energy systems. Global warming is expected to reduce the amplitude and frequency of these climate extremes. We show that the intense cold spells of the 20th century will become nearly impossible in France by the end of the 21st century for high warming levels. We also demonstrate that events in France as intense as that in 1985 may still occur in the near future. These events are linked to specific atmospheric patterns that bring cold air from high latitudes into Europe.

Storms strongly resembling hurricanes are sometimes observed to form well outside the tropics, even in polar latitudes. They behave capriciously, developing very rapidly and then dying just as quickly. We show that strong dynamical processes in the atmosphere can sometimes cause it to become much colder locally than the underlying ocean, creating the conditions for hurricanes to form but only over small areas and for short times. We call the resulting storms "CYCLOPs".

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.

Winter windstorms are the main natural hazard for Generali France. We present a method linking storm events to insurance claims, with a focus on clustered events (multiple storms hitting the same region within 96 h). These account for 85 % of losses since 1998 and include major events like Lothar and Klaus. Damaging storms are twice as likely to occur in clusters, underlining the need to account for their impact in risk, loss, and reinsurance modelling.

Explosive cyclones and atmospheric rivers are two main drivers of extreme weather in Europe. In this study, we investigate their joint changes in future climates over the North Atlantic. Our results show that both the concurrence of these events and the intensity of atmospheric rivers increase by the end of the century across different future scenarios. Furthermore, explosive cyclones associated with atmospheric rivers last longer and are deeper than those without atmospheric rivers.

Extreme cold winter temperatures in Europe have huge societal impacts. This study focuses on extreme cold events, such as the winter of 1963 in France, which are expected to become rarer due to climate change. We use a light and efficient rare-event algorithm to simulate a large number of extreme cold winters over France to analyse their characteristics. We find that despite fewer occurrences, their intensity remains steady. We analyse prevailing atmospheric circulation during these events.

Winter temperatures in central Europe have increased. But cold winters can still cause problems for energy systems, infrastructure, or human health. Here we tested whether a record-cold winter, such as the one observed in 1963 over central Europe, could still occur despite climate change. The answer is yes: it is possible, but it is very unlikely. Our results rely on climate model simulations and statistical rare event analysis. In conclusion, society must be prepared for such cold winters.

We introduce ClimaMeter, a tool offering real-time insights into extreme-weather events. Our tool unveils how climate change and natural variability affect these events, affecting communities worldwide. Our research equips policymakers and the public with essential knowledge, fostering informed decisions and enhancing climate resilience. We analysed two distinct events, showcasing ClimaMeter's global relevance.

We analyse the duration of large-scale patterns of air movement in the atmosphere, referred to as persistence, and whether unusually persistent patterns favour warm-temperature extremes in Europe. We see no clear relationship between summertime heatwaves and unusually persistent patterns. This suggests that heatwaves do not necessarily require the continued flow of warm air over a region and that local effects could be important for their occurrence.

We present a simple system to forecast the Madden–Julian Oscillation (MJO). We use atmospheric circulation as input to our system. We found a good-skill forecast of the MJO amplitude within 40 d using this methodology. Comparing our results with ECMWF and machine learning forecasts confirmed the good skill of our system.

We analyze the atmospheric circulation leading to impactful extreme events for the calendar year 2021 such as the Storm Filomena, Westphalia floods, Hurricane Ida and Medicane Apollo. For some of the events, we find that climate change has contributed to their occurrence or enhanced their intensity; for other events, we find that they are unprecedented. Our approach underscores the importance of considering changes in the atmospheric circulation when performing attribution studies.

The objective motivating this study is the assessment of the impacts of winter climate extremes, which requires accurate simulation of snowfall. However, climate simulation models contain physical approximations, which result in biases that must be corrected using past data as a reference. We show how to exploit simulated temperature and precipitation to estimate snowfall from already bias-corrected variables, without requiring the elaboration of complex, multivariate bias adjustment techniques.

We evaluated the skill of a stochastic weather generator (SWG) to forecast precipitation at different time scales and in different areas of western Europe from analogs of Z500 hPa. The SWG has the skill to simulate precipitation for 5 and 10 d. We found that forecast weaknesses can be associated with specific weather patterns. The comparison with ECMWF forecasts confirms the skill of our model. This work is important because it provides information about weather forecasts over specific areas.

Climate change is already affecting weather extremes. In a warming climate, we will expect the cold spells to decrease in frequency and intensity. Our analysis shows that the frequency of circulation patterns leading to snowy cold-spell events over Italy will not decrease under business-as-usual emission scenarios, although the associated events may not lead to cold conditions in the warmer scenarios.

This study downscales climate information from EURO-CORDEX (approx. 12 km) output to a higher horizontal resolution (approx. 3 km) for the south of France. We also propose a matrix of different indices to evaluate the high-resolution precipitation output. We find that a higher resolution reproduces more realistic extreme precipitation events at both daily and sub-daily timescales. Our results and approach are promising to apply to other Mediterranean regions and climate impact studies.

Present climate models discuss climate change but show no sign of bifurcation in the future. Is this because there is none or because they are in essence too simplified to be able to capture them? To get elements of an answer, we ran a laboratory experiment and discovered that the answer is not so simple.

This paper presents a model of tree ruin as a response to drought hazards. This model is inspired by a standard model of ruin in the insurance industry. We illustrate how ruin can occur in present-day conditions and the sensitivity of ruin and time to ruin to hazard statistical properties. We also show how tree strategies to cope with hazards can affect their long-term reserves and the probability of ruin.

Machine learning approaches are spreading rapidly in climate sciences. They are of great help in many practical situations where using the underlying equations is difficult because of the limitation in computational power. Here we use a systematic approach to investigate the limitations of the popular echo state network algorithms used to forecast the long-term behaviour of chaotic systems, such as the weather. Our results show that noise and intermittency greatly affect the performances.