This study explores whether and why a warmer climate induces alterations in climatological statistics and the underlying physical features of lee cyclogenesis in the Euro-Mediterranean region. The investigation focuses on a specific cyclogenesis type, wherein orography (the Alps), influences the spatial structure and growth rate of the cyclone. This regional scale phenomenon is inspected within the framework of a general weakening and poleward shift of the mid-latitude jet. This large-scale signal, despite being evident in zonal-averaged results from the majority of climate models, remains subject to considerable uncertainty when specific regions and seasons are considered. This uncertainty stems from the intricate interplay and delicate equilibrium among numerous competing mechanisms. The analysis focuses on historical and future trends during the cold semesters across the Euro-Mediterranean region. The historical period is examined using ERA5 reanalysis spanning from 1940 to the present, supplemented by a higher-resolution regional reanalysis product (COSMO-REA6) at approximately 6 km resolution, covering the period 1995-2019 over the Euro-CORDEX (EUR11) domain. State-of-the-art high-resolution climate models are employed to assess historical reproducibility and future trends through an ensemble of global climate models from the HighResMIP initiative. Methodologically, two distinct approaches are pursued. Firstly, changes in statistical properties of lee cyclogenesis are examined, along with composites of precipitation and wind extremes footprint, utilizing two tracking algorithms: TempestExtremes (Ullrich et al., 2021) and TRACK (Hodges, 1994). These algorithms differ in their identification/tracking variables, i.e., mean sea level pressure and 850hPa relative vorticity, respectively. Secondly, an empirical orthogonal function (EOF) analysis is employed to evaluate whether dominant spatial patterns of relevant variables (e.g., mean sea level pressure and 500hPa geopotential height) associated with cyclogenesis undergo significant changes across different time segments. This investigation is conducted as a spin-off of the Copernicus-ECMWF-funded contract C3S2_413 - Enhanced Operational Windstorm Service. The findings aim to enhance our understanding of the complex dynamics of Euro-Mediterranean lee cyclogenesis in the context of a changing climate, providing further insights for climate science and operational windstorm services.

Marine heatwaves, extended periods of elevated sea surface temperature, impact society and ecosystems, and deeper understanding of their drivers is needed to predict and mitigate adverse effects. These events can be particularly severe in the Mediterranean Sea during the summer although the factors that control their occurrence and duration are not fully known. Here we use a comprehensive multi-decadal macroevent dataset and a cluster analysis to investigate the atmospheric dynamics preceding the largest summer marine heatwaves in the Mediterranean Sea. Our study identifies the favourable conditions leading up to marine heatwave peaks and reveals that their main synoptic cause in the Mediterranean Sea is the combined effect of persistent subtropical anticyclonic ridges and associated weakening of prevailing wind systems. When persistent subtropical ridges are established over the region, the resulting decrease in wind speeds causes a substantial reduction in latent heat loss to the atmosphere, which accounts for over 70% of the total heat flux in affected regions. This reduction, combined with a moderate increase in short-wave radiation, generates and intensifies marine heatwaves. This synergistic relationship represents a key mechanism that is critical for skilfully predicting such atmospheric circulation patterns and realistically simulating their impacts on the marine environment.

Temperature extreme events, associated with major impacts on various socioeconomic sectors, exhibit trends related to global warming and undergo important variability across different timescales. While attention has been given to seasonal and decadal predictions, there is growing interest in exploring the potential for skillful predictions also at interannual timescales. In the current study, we assess the skill of the Community Earth System Model-Seasonal-to-Multiyear Large Ensemble in predicting temperature extremes, globally and in all calendar seasons, up to two years ahead. This ensemble of 24 month-long hindcasts enables a comprehensive assessment of interannual predictability, since it is initialized quarterly per year. The study evaluates the capability of the prediction system to forecast the number of days in episodes of extreme temperature anomalies, considering such anomalies in all calendar seasons and studying each forecast season independently. In general, significant predictive skill is found over many regions, depending on the calendar season. As expected, the skill is higher in the first forecast season and generally decreases over time. However, notable skill persists in some regions even up to forecast-season seven. Importantly, in certain regions, significant skill remains up to approximately forecast-season four, even after removing the externally forced signal as estimated from the corresponding uninitialized historical simulations. This suggests that in certain areas, internal variability of the coupled ocean–land–atmosphere system contributes to the predictability of temperature extremes even beyond the seasonal timescale. The role of El Niño–Southern Oscillation as a source of predictability is also assessed and is found to contribute significantly, especially for the boreal winter (DJF) and spring (MAM) up to forecast-season four. However, there is evidence that additional sources of predictability may contribute.

Abstract. In this work, we present and preliminarily evaluate a novel dataset of European windstorms associated with extratropical cyclones (ETCs) based on the whole ERA5 reanalysis period (1940–present). This dataset is produced within the Copernicus Climate Change Service (C3S) Enhanced Operational Windstorm Service (EWS), to promote a knowledge-based assessment of the nature and temporal evolution of European windstorms associated with ETC. Such a dataset is primarily thought to provide high-quality, standardized data on windstorms that support various industries, particularly insurance and risk management, by offering insights into the intensity, density spatial patterns, and, if coupled downstream, with vulnerability and exposure information, the impact of windstorms. EWS includes two datasets: windstorm tracks, based on two tracking algorithms (TRACK and TempestExtremes), and windstorm footprints, produced considering both original-resolution ERA5 variables and statistically downscaled ERA5 variables, with a target grid at 1 km resolution. A preliminary analysis of the datasets shows increasing number of cold-semester windstorms and the associated footprint wind gusts magnitude over a portion of the European territory. The choice of the tracking algorithm is shown to be an important factor in the decision-making process, as it results in non-negligible uncertainties in main windstorm statistics.

The North Atlantic Oscillation (NAO) represents the dominant mode of atmospheric circulation variability over the North Atlantic, driving winter weather conditions over a large part of the Euro-Mediterranean sector. Seasonal forecast systems have demonstrated some predictive skill for wintertime NAO, related to the enhanced ability of dynamical models to correctly represent possible sources of NAO predictability. However, increasing the predictive skill at the seasonal timescale over the European domain is still considered a major challenge.In this work the aim is to extract the potential hidden skill in a dynamical seasonal forecast ensemble by properly selecting relevant realizations. The idea is to define a reduced ensemble better performing in terms of NAO predictions and to assess the performance of this subsample compared to the full ensemble.Different subsampling criteria have been tested and verified. On the one hand, under the assumption that the ensemble average represents the most predictable path, the members simulating at the beginning of the forecast a NAO state closest to the ensemble mean NAO are selected. On the other hand, the realizations that resemble a reliable and independent estimate of the winter NAO, derived from the autumn conditions of a set of established dynamical predictors, are taken into consideration.The comparison between the results obtained with the full ensemble and these subsampled ensembles reveals the potential for a significant improvement in the prediction of 2m temperature and precipitation anomalies, therefore representing a valuable strategy for possible real-time operational applications both in a multi-model and in a single model framework.

Accurate predictions of climate variations at the decadal timescale are of great interest for decision-making, planning and adaptation strategies for different socio-economic sectors. Notably, decadal predictions have rapidly evolved during the last 15 years and are now produced operationally worldwide. The majority of the studies assessing the skill of decadal prediction systems focus on time-mean anomalies of standard meteorological variables, such as annual mean near-surface air temperature and precipitation. However, the predictability of extreme events frequency may differ substantially from the predictability of multi-year annual or seasonal means. Predicting the frequency of extreme events at different timescales is of major importance, since they are associated with severe impacts on various natural and human systems. In the current study we evaluate the capability of state-of-the-art decadal prediction systems to predict the frequency of temperature extremes in Europe. More specifically, we assess the skill of a multi-model ensemble from the Decadal Climate Prediction Project (DCPP, 163 ensemble members from 12 models in total) to forecast the number of days belonging to heatwaves episodes during summer (June–August). We find statistically significant predictive skill over Europe, except for the United Kingdom and a large part of the Scandinavian Peninsula, most of which is associated with the long-term warming trend. We are progressing with the evaluation of other statistical aspects of extreme events, including warm and cold episodes during winter, and we are also investigating whether there is predictive skill beyond that stemming from the external forcing.

Understanding the natural and forced variability of the general circulation of the atmosphere and its drivers is one of the grand challenges in climate science. In particular, it is of paramount importance to understand to what extent the systematic error of global climate models affects the processes driving such variability. This is done by performing a set of simulations (ROCK experiments) with an intermediate complexity atmospheric model (SPEEDY), in which the Rocky Mountains orography is modified (increased or decreased) to influence the structure of the North Pacific jet stream. For each of these modified-orography experiments, the climatic response to idealized sea surface temperature (SST) anomalies of varying intensity in the El Niño Southern Oscillation (ENSO) region is studied. ROCK experiments are characterized by variations in the Pacific jet stream intensity whose extension encompasses the spread of the systematic error found in state-of-the-art climate models. When forced with ENSO-like idealised anomalies, they exhibit a non-negligible sensitivity in the response pattern over the Pacific North American region, indicating that a change/bias in the model mean state can affect the model response to ENSO. It is found that the classical Rossby wave train response generated by ENSO is more meridionally oriented when the Pacific jet stream is weaker, while it exhibits a more zonal structure when the jet is stronger. Rossby wave linear theory, used here to interpret the results, suggests that a stronger jet implies a stronger waveguide, which traps Rossby waves at a lower latitude, favouring a more zonally oriented propagation of the tropically induced Rossby waves. The shape of the dynamical response to ENSO, determined by changes in the intensity of the Pacific Jet, affects in turn the ENSO impacts on surface temperature and precipitation over Central and North America. Furthermore, a comparison of the SPEEDY results with CMIP6 models behaviour suggests a wider applicability of the results to more resources-demanding, complete climate GCMs, opening up to future works focusing on the relationship between Pacific jet misrepresentation and response to external forcing in fully-fledged GCMs.

Understanding how the general circulation of the atmosphere is affected by global warming is one of the grand challenges in climate science. Climate models are a valuable tool to: i) identifying potential mechanism for changes in general circulation, ii) recognizing signals that can be related to external forcing and iii) produce projections for future scenarios. Despite the use of large ensemble of continuosly improving climate models, uncertainty for the extratropical circulation is still large. It is therefore important to understand processes driving the variability of the circulation in climate models and how these processes are affected by model bias. To characterize the effect of models bias on the response to a given forcing, several simulations were performed with the Simplified Parameterizations, primitivE - Equation DYnamics (SPEEDY), an intermediate complexity model developed by International Center for Theoretical Physics (ICTP). Four simulations are performed with a modified orography in order to obtain an atmospheric circulation at mid-latitudes characterized by different mean states and a control climate simulation carried in standard configuration is used as baseline. For each of these experiments, we have studied the climatic response to El Niño Southern Oscillation (ENSO) and to the Atlantic Multidecadal Variability (AMV). All the Sensitivity simulations were performed with a large ensemble (~100 members). Results show that indeed the model response is non-negligibly influenced by its mean state and reveal geographic areas where the sensitivity is large. On the other hand, they also show large scale regions of the world where the atmospheric response to ENSO and AMV is unlikely to depend on the atmospheric mean state. We also found that the relationship between changes in the model mean state and the response to the forcing appears to be non linear. These results cam be used to interpret and understand multi-model spread in atmospheric response to aforementioned surface condition.

Can multi-annual variations in the frequency of North Atlantic atmospheric blocking and mid-latitude circulation regimes be skilfully predicted? Recent advances in seasonal forecasting have shown that mid-latitude climate variability does exhibit significant predictability. However, atmospheric predictability has generally been found to be quite limited on multi-annual timescales. New decadal prediction experiments from NCAR are found to exhibit remarkable skill in reproducing the observed multi-annual variations of wintertime blocking frequency over the North Atlantic and of the North Atlantic Oscillation (NAO) itself. This is partly due to the large ensemble size that allows the predictable component of the atmospheric variability to emerge from the background chaotic component. The predictable atmospheric anomalies represent a forced response to oceanic low-frequency variability that strongly resembles the Atlantic Multi-decadal Variability (AMV), correctly reproduced in the decadal hindcasts thanks to realistic ocean initialization and ocean dynamics. The occurrence of blocking in certain areas of the Euro-Atlantic domain determines the concurrent circulation regime and the phase of known teleconnections, such as the NAO, consequently affecting the stormtrack and the frequency and intensity of extreme weather events. Therefore, skilfully predicting the decadal fluctuations of blocking frequency and the NAO may be used in statistical predictions of near-term climate anomalies, and it provides a strong indication that impactful climate anomalies may also be predictable with improved dynamical models.

Abstract The atmospheric circulation in the mid-latitudes of both hemispheres is usually dominated by westerly winds and by planetary-scale and shorter-scale synoptic waves, moving mostly from west to east. A remarkable and frequent exception to this “usual” behavior is atmospheric blocking. Blocking occurs when the usual zonal flow is hindered by the establishment of a large-amplitude, quasi-stationary, high-pressure meridional circulation structure which “blocks” the flow of the westerlies and the progression of the atmospheric waves and disturbances embedded in them. Such blocking structures can have lifetimes varying from a few days to several weeks in the most extreme cases. Their presence can strongly affect the weather of large portions of the mid-latitudes, leading to the establishment of anomalous meteorological conditions. These can take the form of strong precipitation episodes or persistent anticyclonic regimes, leading in turn to floods, extreme cold spells, heat waves, or short-lived droughts. Even air quality can be strongly influenced by the establishment of atmospheric blocking, with episodes of high concentrations of low-level ozone in summer and of particulate matter and other air pollutants in winter, particularly in highly populated urban areas. Atmospheric blocking has the tendency to occur more often in winter and in certain longitudinal quadrants, notably the Euro-Atlantic and the Pacific sectors of the Northern Hemisphere. In the Southern Hemisphere, blocking episodes are generally less frequent, and the longitudinal localization is less pronounced than in the Northern Hemisphere. Blocking has aroused the interest of atmospheric scientists since the middle of the last century, with the pioneering observational works of Berggren, Bolin, Rossby, and Rex, and has become the subject of innumerable observational and theoretical studies. The purpose of such studies was originally to find a commonly accepted structural and phenomenological definition of atmospheric blocking. The investigations went on to study blocking climatology in terms of the geographical distribution of its frequency of occurrence and the associated seasonal and inter-annual variability. Well into the second half of the 20th century, a large number of theoretical dynamic works on blocking formation and maintenance started appearing in the literature. Such theoretical studies explored a wide range of possible dynamic mechanisms, including large-amplitude planetary-scale wave dynamics, including Rossby wave breaking, multiple equilibria circulation regimes, large-scale forcing of anticyclones by synoptic-scale eddies, finite-amplitude non-linear instability theory, and influence of sea surface temperature anomalies, to name but a few. However, to date no unique theoretical model of atmospheric blocking has been formulated that can account for all of its observational characteristics. When numerical, global short- and medium-range weather predictions started being produced operationally, and with the establishment, in the late 1970s and early 1980s, of the European Centre for Medium-Range Weather Forecasts, it quickly became of relevance to assess the capability of numerical models to predict blocking with the correct space-time characteristics (e.g., location, time of onset, life span, and decay). Early studies showed that models had difficulties in correctly representing blocking as well as in connection with their large systematic (mean) errors. Despite enormous improvements in the ability of numerical models to represent atmospheric dynamics, blocking remains a challenge for global weather prediction and climate simulation models. Such modeling deficiencies have negative consequences not only for our ability to represent the observed climate but also for the possibility of producing high-quality seasonal-to-decadal predictions. For such predictions, representing the correct space-time statistics of blocking occurrence is, especially for certain geographical areas, extremely important.

This paper reviews the historical development of concepts and practices in the science of ocean predictions. It begins with meteorology, which conducted the first forecasting experiment in 1950, followed by wind waves, and continuing with tidal and storm surge predictions to arrive at the first successful ocean mesoscale forecast in 1983. The work of Professor A. R. Robinson of Harvard University, who produced the first mesoscale ocean predictions for the deep ocean regions is documented for the first time. The scientific and technological developments that made accurate ocean predictions possible are linked with the gradual understanding of the importance of the oceanic mesoscales and their inclusion in the numerical models. Ocean forecasting developed first at the regional level, due to the relatively low computational requirements, but by the end of the 1990s, it was possible to produce global ocean uncoupled forecasts and coupled ocean-atmosphere seasonal forecasts.

Maarten Ambaum, Neil Bowler, Jim Caughey, Andrew Challinor, Andrew Charlton, Rosalind Cornforth, Helen Dacre, Sarah Dance, Huw Davies, Andreas Dörnbrack, John Eyre, Evan Fraser, Alan Gadian, Ricardo García Herrera, Jose Antonio Garcia–Moya, Luis Gimeno, Stuart Goldstraw, Andy Gouldson, Suzanne Gray, Robin Hogan, Klaus-Peter Hoinka, Anthony Illingworth, Thomas Jung, Detlev Majewski, John Marsham, Brian Mills, Thor-Erik Nordeng, Doug Parker, Robert Plant, Ricardo M. Trigo, Mathias Rotach, Conny Schwierz, Mel Shapiro, Lenny Smith, Olivier Talagrand, Emma Tompkins, Hans Volkert, Martin Weissmann, Volker Wulfmeyer, Günther Zängl and Michal Ziemianski

La ricerca che viene qui presentata, alla quale Arpa è orgogliosa di avere contribuito grazie all'impegno del direttore della Sezione pro- vinciale di Modena e dei suoi collaboratori, mette a confronto la per- cezione della criticità di alcuni problemi ambientali con le misure reali dei relativi parametri di rischio, nell'intera città e nei diversi quartieri. L'esito conferma - ma in modo molto argomentato e analiticamente fondato -ciò che, in campo ambientale, l'Agenzia regionale ha verifi- cato in questo decennio di attività. Un antico principio della filosofia "realistica" greca dice che: "non c'è nulla nell'intelletto, che prima non sia stato nei sensi". La conoscenza deriverebbe dunque dall'esperienza diretta, sensoriale. Però, i sensi possono mentirci e spesse volte lo fanno davvero. Abbiamo più e più volte riscontrato che i due mondi, dell'esperienza sensoriale e della misura quantitativa (della conoscenza?), della "qua- lità ambientale percepita" e della "qualità ambientale rilevata" non sempre si sovrappongono. O, meglio, che si possono creare cortocir- cuiti tra esperienza e generalizzazioni intellettuali. Per esempio: la qualità dell'aria che respiriamo è decisamente migliorata, negli ultimi decenni. Non più emissioni di piombo (che è stato eliminato dalle benzine), non più ossidi di zolfo (le famigerate "piogge acide" degli anni '70 sono ormai un ricordo, eliminate dalle marmitte catalitiche), drastico calo degli ossidi di azoto, sostituzione in quasi tutti gli impianti di riscaldamento del gasolio con il metano ecc. Eppure, l'allarme sociale dettato dall'inquinamento atmosferico è oggi assai superiore a quello del passato. Le ragioni? Forse ha inciso l'espe- rienza di un aumento del traffico, forse la scoperta di nuovi importanti parametri fisico-chimici da misurare (le polveri, soprattutto quelle sot- tili) connessi a fenomenologie che minacciano la nostra salute, come l'aumento dell'incidenza percentuale delle malattie respiratorie (ma, quest'ultimo, anche perché si è allungata la vita media e magari anche perché altre cause di malattia sono state affrontate con maggiore suc- cesso), forse la perdita di memoria, per le generazioni più giovani, del- l'inquinamento derivante dagli impianti industriali oggi dismessi o allontanati dai centri urbani e quindi dalla vista ecc. In altri termini, la percezione è relativa alle condizioni specifiche, al contesto, all'evolu- zione storica, ed è condizionata da fattori "confondenti", che si com- portano analogamente a quelli che incidono sui ragionamenti della scienza: producono effetti uguali a quelli prodotti dalle cause che stiamo indagando, e dunque ci inducono ad attribuire tutti gli effetti a quelle stesse cause. Ciò che vale per l'inquinamento atmosferico è vero in misura ancora maggiore per certo inquinamento elettromagnetico, ma assai meno per l'inquinamento acustico. La differenza, ovviamente, sta molto nella "fisicità" della percezione e nell'abitudine all'esposizione, anche non cosciente. La difformità tra qualità ambientale percepita ed esposi- zione della popolazione e del territorio, riferite ai diversi inquinanti e nei diversi quartieri di Modena, rispecchia in buona misura questo gra- duale prevalere di fattori intangibili, spesso inversamente proporzio- nale alla "materialità" dell'inquinante considerato.