Atmospheric transport processes over mountainous terrains are intrinsically affected by a variety of landforms, surface covers, atmospheric stability situations and interactions among different airflows, typical occurring on multiple space and time scales. Our understanding of the interplay of such factors is still far from being fully understood. In particular, the peculiar properties of atmospheric turbulence controlling the exchanges of momentum, heat and mass between the land surface, the atmospheric boundary layer and upper levels are still largely unexplored.

As a contribution to filling these gaps, the research project DECIPHER implemented observational and modelling actions aimed at disentangling mechanisms controlling atmospheric transport and mixing processes over mountain areas at different space- and timescales, in the framework of the larger international research effort TEAMx (Serafin et al. 2018, Rotach et al. 2021).

As part of the project, field measurements were performed at selected areas to investigate transport and exchange processes associated with thermally-driven slope winds and other local winds, and their connections with various ambient and weather conditions.

In particular, an intensive field campaign was organised over an east-facing steep slope of Monte Baldo (45°39'56.0"N, 10°49'10.9"E), an approximately north-south oriented mountain range in the Southern Alps. Several different instruments were operated from mid-June to mid-October 2025 to cover atmospheric processes at different scales. Turbulent processes were monitored through multi-level flux towers installed at different elevations, along with thermohygrometers distributed along the slope to capture the vertical structure of the ambient atmosphere. Mass and optical sensors monitored concentrations and properties of particulate matter. The 3-D structures of local along- and cross-slope winds and vertical temperature profiles were also observed with multiple wind lidars based at different points. Moreover, tropospheric profiles were obtained from a tethered balloon and a Raman lidar. Further non-conventional measurements included high-frequency profiling of turbulence near the surface and distributed soil moisture monitoring using a cosmic-ray neutron sensor.

Preliminary outcomes from the analysis of the resulting huge dataset allow for identifying interesting patterns of local circulations and their connections with turbulence structure, as well as with the surrounding flow and stability conditions, under different weather situations.

Besides research achievements, DECIPHER was also a remarkable and unique opportunity to consolidate relationships of scientific cooperation among the numerous partners involved, and to successfully test new observational techniques and logistic solutions for the nontrivial deployment of such a major field campaign. Hence it contributed to build-up It was a great opportunity for growing a scientific community characterised by complementary expertise, a remarkable amount of personnel involved, and the numerosity and diversity of instruments enabled to plan and perform the unusual effort adequate for phenomena, whose complexity would not be captured with any fewer instruments. Buildup of a scientific community

References

Rotach, M.W., Serafin, S., Ward, H.C., Arpagaus, M., Colfescu, I., Cuxart, J., De Wekker, S.F.J., Grubišic, V., Kalthoff, N., Karl, T., Kirshbaum, D.J., Lehner, M., Mobbs, S., Paci, A., Palazzi, E., Bailey, A., Schmidli, J., Wittmann, C., Wohlfahrt, G. and Zardi, D. (2022): A collaborative effort to better understand, measure and model atmospheric exchange processes over mountains. Bulletin of the American Meteorological Society. https://doi.org/10.1175/BAMS-D-21-0232.1

Serafin, S., Adler, B., Cuxart, J., De Wekker, S.F.J., Gohm, A., Grisogono, B., Kalthoff, N., Kirshbaum, D.J., Rotach, M.W., Schmidli, J., Stiperski, I., Večenaj, Ž. and Zardi D. (2018): Exchange Processes in the Atmospheric Boundary Layer Over Mountainous Terrain. Atmosphere, 9, 102. https://doi.org/10.3390/atmos9030102

Studi recenti di eventi di precipitazioni estreme e alluvioni che hanno interessato l’Italia centro-settentrionale e l’area alpina in particolare hanno rivelato che oltre al contributo locale dovuto all’evaporazione dal Mar Mediterraneo, una quantità rilevante di umidità può giungere da regioni remote per mezzo di un intenso trasporto confinato all’interno di corridoi lunghi e stretti, noti come fiumi atmosferici.

Il progetto nazionale ARMEX, finanziato nell’ambito PRIN2022 dal Ministero dell’Università e della Ricerca, ha l’obiettivo di esplorare i fiumi atmosferici nel Mediterraneo e la loro connessione con eventi idrometeorologici estremi sull’Italia. Il progetto coinvolge competenze sia nella modellistica meteorologica e idrologica, sia nel monitoraggio da satellite. Vengono qui presentati alcuni risultati del progetto.

Utilizzando le rianalisi ERA5 e il dataset di precipitazioni ArCIS, e applicando un algoritmo di identificazione, opportunamente adattato alla peculiare e complessa morfologia della regione, è stato possibile evidenziare le principali caratteristiche climatologiche dei fiumi atmosferici nel Mediterraneo e la loro connessione con eventi idrometeorologici estremi sul centro-nord Italia dal 1960 ad oggi. Inoltre, attraverso l’analisi di diversi casi studio, simulazioni numeriche ad alta risoluzione hanno dimostrato che la presenza di un intenso fiume atmosferico – proveniente dalle aree tropicali dell’Africa o dall’Atlantico – rappresenta un elemento distintivo degli eventi estremi. Gli esperimenti modellistici hanno permesso di investigare le caratteristiche, i meccanismi dinamici e gli impatti dei fiumi atmosferici, i quali si sono rivelati un ingrediente fondamentale per il verificarsi di precipitazioni estreme. Infine, si sta esplorando la predicibilità a scala sub-stagionale di eventi estremi caratterizzati dalla presenza di fiumi atmosferici.

The thermal and moisture regimes of coastal cities arise from the interplay between mesoscale atmospheric circulations and local urban form, creating highly heterogeneous microclimates that directly affect heat exposure, energy demand, and outdoor comfort. This study presents an integrated multi-source approach to evaluate thermo-hygrometric variability in Bari (southern Italy), a representative Mediterranean coastal city characterized by strong land–sea interactions. The analysis combines in situ observations, remote-sensing data, and urban-canopy modelling to disentangle the relative roles of mesoscale forcing and microscale heterogeneity. Eight canyon-level sensors were deployed across districts with distinct morphology, vegetation density, and distance from the coastline, continuously monitoring air temperature and, at five sites, relative humidity during the summer of 2023. These measurements were complemented with high-resolution ECOSTRESS land-surface-temperature (LST) data and numerical simulations from the Multi-Layer Urban Canopy Model (MLUCM BEP+BEM) driven by ERA5 reanalysis. Morphological and radiative parameters around each site were quantified within a 500 m radius following the Local Climate Zone (LCZ) classification. Statistical analyses based on repeated-measures ANOVA quantified temporal and spatial variability in air temperature and humidity, enabling a robust assessment of the significance of observed differences. Results show that nocturnal temperature differences across Bari are relatively limited (< 2 °C), while after sunrise, the development of a sea–land-breeze circulation induces marked divergence among sites. Inland neighbourhoods warm and dry rapidly, reaching up to 5–6 °C higher air temperatures than coastal areas, which remain moderated by maritime ventilation. Conversely, relative humidity exhibits an inverse pattern, increasing along the coastline and decreasing inland. Evening cooling is slower in dense central districts due to greater heat storage, a pattern also captured by ECOSTRESS LST data. These findings highlight the dual control exerted by mesoscale dynamics and local morphology, with compact built-up zones and impervious surfaces amplifying daytime heat accumulation and delaying nocturnal release. Simulations with MLUCM BEP+BEM reproduce the observed intra-urban variability with notable accuracy, outperforming ERA5 near-surface reanalysis fields. Model-sensitivity tests demonstrate that the choice of boundary forcing significantly affects MLUCM BEP+BEM performance: sea-based forcings yield the best agreement near the coastline, while interpolated configurations perform better inland. Across all scenarios, the model captures microscale-driven variability of comparable magnitude to mesoscale contributions, confirming its suitability for reproducing canopy-layer processes under different urban and meteorological conditions. Overall, this research demonstrates that integrating mesoscale and microscale datasets provides a coherent framework for interpreting the spatial structure of thermal and moisture fields in coastal cities. The multi-source methodology—combining field measurements, satellite observations, and a physics-based urban-canopy model—offers a transferable approach for diagnosing urban heat exposure and informing climate adaptation. In particular, the MLUCM BEP+BEM model proves effective in distinguishing coastal–inland gradients and quantifying the influence of urban form and land cover on local climate. These results underscore the need for multiscale assessments to support energy-efficient urban design, improve outdoor comfort, and enhance resilience strategies in Mediterranean coastal environments increasingly exposed to heat stress and climate change.

Acknowledgements: This work is supported by ICSC – Centro Nazionale di Ricerca in High Performance Computing, Big Data and Quantum Computing, funded by European Union – NextGenerationEU (CUP F83C22000740001).

Reference: Pappaccogli, G., Zonato, A., Martilli, A., Buccolieri, R., and Lionello, P.: MLUCM BEP+BEM: An offline one-dimensional Multi-Layer Urban Canopy Model based on the BEP+BEM Scheme, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-219, 2025.

The project “Urban hEat and pollution iSlands inTerAction in Rome and possible mitigation strategies” (RESTART), funded by the Italian Ministry of University and Research within the PRIN program, investigates the interplay between the Urban Heat Island (UHI) and the Urban Pollution Island (UPI) in Rome over the period 2019-2024. At its concluding stage, the project provides new insights into the drivers and feedbacks linking these phenomena and proposes tailored Nature-Based Solutions (NBS) to improve urban liveability and resilience.

High-temporal resolution meteorological and air quality observations from monitoring networks and international observatories were analysed to assess the current state of UHI and UPI and their links under different meteorological conditions. The analysis confirms that their interaction is strongly modulated by meteorological conditions, with combined effects intensifying during heatwaves and calm wind days.

To capture these dynamics, RESTART employed an innovative multiscale modelling framework that couples the Weather Research and Forecasting (WRF) mesoscale model with the ADMS-Urban dispersion model. This chain proved effective in reproducing spatial patterns of meteorological variables and pollutant concentrations, and in evaluating the role of NBS under both current and mitigation scenarios.

In this contribution, the science-based recommendations derived from the project will be discussed. Specifically, the outcomes emphasize the potential of NBS (i.e., urban greening and tree planting) to simultaneously mitigate heat stress and pollution accumulation. By combining high-quality monitoring data with advanced numerical simulations, RESTART contributes to the design of tailored, evidence-based mitigation strategies supporting sustainable and climate-resilient urban planning.

To conclude, the integrated observation–modelling approach developed in RESTART represents not only a valuable decision-support tool for the city of Rome, but also a transferable methodology applicable to other urban areas facing similar climate and air quality challenges.

Le micro- e nanoplastiche (MNP) stanno emergendo come una nuova e pervasiva componente degli aerosol atmosferici, ma le loro origini, i meccanismi di trasporto e il destino finale nell’atmosfera rimangono in gran parte sconosciuti. A differenza delle particelle aerosol convenzionali, esse derivano da una complessa combinazione di sorgenti continentali, marine e secondarie, e il loro comportamento fisico dipende in modo critico da dimensioni, forma e tipo di polimero.
Nonostante la crescente attenzione scientifica, i dati osservativi disponibili sono ancora scarsi e frammentari, raccolti in ambienti eterogenei e mediante metodologie analitiche non uniformi, rendendo difficile ottenere una visione coerente e comparabile del fenomeno.

In questo lavoro vengono analizzate le possibili sorgenti e traiettorie di trasporto atmosferico delle MNP, con l’obiettivo di identificare i processi dominanti che ne controllano la variabilità spaziale e temporale. A partire da osservazioni provenienti da ambienti urbani, suburbani, montani e nuvolosi, lo studio combina l’utilizzo dell’ultima versione del modello di dispersione lagrangiano FLEXPART v11 (adattato per le MNP) con una analisi statistica multi livello, basata su correlazioni e modelli di regressione multipla, per esplorare le relazioni tra le concentrazioni osservate e un insieme di proxy su larga scala rappresentativi delle diverse sorgenti potenziali (suoli agricoli e aridi, aree popolate, spray marino), considerando differenti età di trasporto atmosferico (1–45 giorni).

I risultati indicano che gli indicatori antropici e continentali (popolazione, aree irrigate) presentano correlazioni positive e persistenti soprattutto a brevi tempi di trasporto, mentre le sorgenti a più lungo raggio sembrano essere legate a emissioni di tipo marino e da zone aride. I modelli di regressione evidenziano driver regionali eterogenei e il potenziale contributo del trasporto a lunga distanza evidenziato dai siti montani.

Nel complesso, i risultati dimostrano che, pur in presenza di forti limitazioni osservazionali, è possibile estrarre segnali fisicamente coerenti, fornendo nuove evidenze sui processi che governano la presenza e la trasformazione delle MNP nell’atmosfera, e sottolineando la necessità di miglioramenti nelle tecniche di osservazione e di una maggiore copertura spaziale dei dati.

The rising frequency and severity of compound hydro-meteorological extremes underscore the urgent need to better understand their dynamics and occurrence. Compound events, involving concurrent or sequential natural hazards, often lead to amplified impacts compared to individual events. A recent striking example is the exceptional sequence of heavy rainfall in northern Italy (2023–2024), which triggered widespread flooding in Emilia-Romagna. Flood severity and extent were compounded by prior soil saturation resulting from earlier rainfall, illustrating how antecedent conditions can exacerbate impacts. However, the rarity and unprecedentedness of such events limits their representation in observational records owing to their limited temporal coverage, hence posing substantial challenges for robust statistical characterization. To overcome this, the UNSEEN (Unprecedented Simulated Extremes using ENsembles) approach has recently emerged. UNSEEN is employed by pooling large ensembles of seasonal re-forecasts from numerical weather prediction models to create synthetic time series spanning thousands of years. This enables the analysis of low-probability, high-impact events and the investigation of their dynamical features within a statistically robust framework.

This study applies the UNSEEN methodology to compound flood events within a multivariate framework, focusing on the interaction between precipitation and soil moisture as a key preconditioning driver. Seasonal re-forecasts from the SEAS5 dataset (ECMWF) over 1994-2023 are considered to characterize unprecedented compound floodings in Emilia Romagna. As a first step, the UNSEEN ensemble's ability to represent univariate extremes is assessed to ensure the reliability of the pooled surrogate time series. The surrogate series is then analyzed to distinguish precipitation extremes occurring with and without soil-moisture pre-conditioning, enabling a detailed assessment of their interaction and the associated hydrological responses within the regional river catchments. Results indicate that the UNSEEN ensemble realistically reproduces historical extreme flood events, offering a more robust characterization than observational records alone. Additionally, the river discharge response further differentiates the two event classes, with pre-conditioned events consistently leading to higher river levels, underscoring the amplifying role of antecedent soil moisture to the hydrological system. These findings highlight the value of ensemble-based approaches for better understanding rare compound events and informing more effective adaptation and mitigation strategies in flood-prone areas.

Medicanes are high-impact cyclones whose frequency may decline but whose strongest events may intensify in a warming Mediterranean (Romero et al., 2017; Tous et al., 2016). Medicane Ianos (September 2020) stands out as the strongest event on record, causing severe flooding and coastal damage across the Ionian Sea.

We analyze Medicane Ianos using a vertically integrated Moist Static Energy (MSE) variance budget as a process-based diagnostic of convective–dynamical coupling. ERA5 fields are tracked objectively, phases are classified in Hart phase space, and the budget is evaluated over ~2.5×10⁵ km² along the storm’s track. The intensification of Ianos is explained by a delicate balance between vertical moistening and horizontal advection, with surface latent-heat fluxes and radiative tendencies reinforcing the MSE build-up during the mature stage. The energy structure is tropical-like within ~600 km of the center during peak intensity, supporting medicane classification (Flaounas at al., 2022).

We extend this framework by using MSE variance as a convective metric across ensembles to link energetics to track and phase uncertainty. With the ECMWF IFS ensemble with perturbed physical parameterizations, forecast spread in trajectories and transition timing correlates with early-time MSE-tendency components and with the interaction between upper-level PV streamers and near-surface thermodynamic disequilibrium (Saraceni et al., 2023, ACP). This combined approach—MSE-budget + ensemble diagnostics—clarifies when medicanes behave more “tropical-like” (dominant convective moistening) versus “subtropical” (strong baroclinic/advection control), informing the ongoing classification debate.

References

Saraceni, M., Silvestri, L., & Bongioannini Cerlini, P. (2025). Analyzing the Mediterranean Tropical-like Cyclone Ianos Using the Moist Static Energy Budget. Atmosphere, 16(5), 562. https://doi.org/10.3390/atmos16050562

Saraceni, M., Silvestri, L., Bechtold, P., & Bongioannini Cerlini, P. (2023). Mediterranean tropical-like cyclone forecasts and analysis using the ECMWF ensemble forecasting system with physical parameterization perturbations. Atmospheric Chemistry and Physics, 23, 13883–13909. https://doi.org/10.5194/acp-23-13883-2023

Flaounas, E., Davolio, S., Raveh-Rubin, S., Pantillon, F., Miglietta, M. M., Gaertner, M. A., Hatzaki, M., Homar, V., Khodayar, S., Korres, G., et al. (2022). Mediterranean cyclones: Current knowledge and open questions on dynamics, prediction, climatology and impacts. Weather and Climate Dynamics, 3(1), 173–208. https://doi.org/10.5194/wcd-3-173-2022

Romero, R., Gaertner, M. A., Sánchez, E., Domínguez, M., González-Alemán, J. J., Miglietta, M. M., Walsh, K. J., Gil, V., Padorno, E., Picornell, M. A., & Romero, R. (2017). Climate change projections of medicanes with a large multi-model ensemble of regional climate models. Global and Planetary Change, 151, 134–143. https://doi.org/10.1016/j.gloplacha.2016.10.008

Tous, M., Romero, R., & Ramis, C. (2016). Projected changes in medicanes in the HadGEM3 N512 high-resolution global climate model. Climate Dynamics, 47(3–4), 1357–1372. https://doi.org/10.1007/s00382-015-2901-7

A comparative study of Medicane Daniel (September 2023) is performed using two high-resolution models, WRF and ICON, both configured at ∼2 km spatial resolution with comparable domains, timesteps, boundary forcing and settings. A custom optimizer harmonizes the vertical levels discratization and sensitivity experiments test different cumulus parametrizations: fully explicit, shallow-convection, deep-cumulus parameterized and ICON’s gray-zone option. Diagnostics include an objective tracker combining mean sea-level pressure and lower-tropospheric geopotential, alongside intensity metrics (central pressure and 10 m wind), precipitation patterns and point validation at Benina (HLLB) for pressure, wind and rainfall. Structural evolution is assessed through Hart’s Cyclone Phase Space (CPS) and a novel Temporal Annular Symmetric Mean (TASM), describing the three-dimensional storm structure during its warm-core phase. Both models reproduce Daniel’s track, lifecycle and tropical-like features. Explicit convection deepens the cyclone and sharpens wind maxima, but enhances small-scale variability that complicates tracking. Deep-cumulus schemes weaken extremes and broaden rainfall, while shallow-convection options provide a balance, improving precipitation placement and core thermodynamics. Model internal differences also influence results: ICON shows lower efficiency in transferring diabatic heating upward, producing a shallower warm core, whereas WRF tends to generate a stronger vortex to better retain tropical-like characteristics. CPS and TASM consistently indicate a shallow-to-deep warm-core transition and a compact, symmetric structure at peak intensity. Overall, the study highlights the importance of harmonized configurations and suggests that, at gray-zone resolutions, shallow-convection treatments often offer a good compromise for simulating Mediterranean tropical-like cyclones.

We analyze 17 Mediterranean cyclones with tropical characteristics using ERA5
reanalysis data to investigate the role of upper-tropospheric processes and their
seasonal variations in cyclone development. Our results show that cyclones
occurring in September exhibit the strongest moist convection, with Ianos, one
of the strongest medicanes on record, representing an extreme case. The devel-
opment of the warm core is anticorrelated with the value of upper-tropospheric
potential vorticity (PV), and correlated with lower tropospheric PV associated
with latent heat release. Using back-trajectories analysis, we then investigate the
presence of dry intrusions in the early and mature cyclone phases. We show that
the Lagrangian definition of dry intrusion, characterized by a descent of 400 hPa
in 48 hours, is not satisfied in most of the cyclones considered here. Instead,
weaker PV streamers with shallower descent are often observed before cycloge-
nesis. While a dry intrusion may reduce static stability and intensify convection,
leading to an accelerated warm core formation, the eventual warm core intensity
appears to depend critically on pre-existing convection and diabatic heating in
a close vicinity of the cyclone center. This is the case for Medicane Ianos. In
fact, this cyclone presents two marginally descending flows of about 200 hPa
in 60 hours associated with shallow PV streamers, one in the early stage and
one before the main tropical-like phase. Despite the modest intensity of the
PV streamer, Ianos develops the strongest warm core among all cyclones. This
motivates us to examine Ianos in detail using a WRF simulation with a grid
spacing of 3 km. The simulation confirms the need for a high-resolution model
setup to correctly represent the cyclone intensity and capture key mesoscale
mechanisms and the dominant contribution of diabatic heating to the cyclone
deepening.

Wet-snow events are a major cause of severe winter outages in the Italian high- and medium-voltage power networks, due to the accumulation of ice and snow on overhead conductors. It is estimated that, in Italy alone, the annual economic impact of these events exceeds 200 million euros.

To address this issue, RSE initiated a research program more than a decade ago that led to the development of an operational alert system for snow accumulation on overhead lines. The system, known as WOLF (Wet-snow Overload aLert and Forecasting), is designed to forecast wet-snow loads on overhead lines during snowfall events and to provide timely warnings to Italian TSOs and DSOs, enabling them to implement appropriate measures to ensure the reliability and continuity of electricity transmission and distribution. WOLF integrates precipitation and temperature fields from the WRF model with the Makkonen accretion model, which estimates the growth of snow load on a reference conductor in each domain grid cell as a function of the prevailing meteorological conditions.

Over the past ten years, observations collected at the WILD (Wet-snow Ice Laboratory Detection) monitoring station, located in the Cuneo Alps, have supported the refinement of both meteorological forecasting models and snow-sleeve accretion models. Previous case studies have shown that the primary sources of uncertainty in snow-load forecasts stem from the intrinsic limitations of the meteorological fields simulated by the NWP models used to drive the accretion model. Sensitivity analyses performed using different model configurations and global drivers revealed variable performance, without identifying a single optimal setup across the analyzed snowfall events.

The recent availability of NWP model outputs from multiple providers through the Italian open-data hub Mistral (https://meteohub.mistralportal.it/app/datasets) offers new opportunities to address these limitations. In this work, the potential benefits of a multi-model approach are assessed by combining snow-load forecasts derived from different meteorological simulations and by exploring probabilistic post-processing techniques for wet-snow prediction. The results, validated against observations from recent snowfall events in the Alpine region, indicate that this approach is promising. Further research is planned, including evaluation over a larger set of case studies, with the aim of reducing the forecast uncertainty of the WOLF system starting from upcoming winter seasons.

The Solar Wind-Magnetosphere-Ionosphere coupling constitutes an important subject of scientific interest, in particular in the Space Weather context. Briefly, in this process, the energy is transferred from the solar wind to the magnetosphere by means of both the magnetic reconnection at the dayside magnetopause and the viscous-like interaction generated by micro or macro instabilities. On the other hand, the magnetosphere and the ionosphere, strictly connected through the magnetic field lines, can exchange energy and momentum, basically, through three main processes: (1) the transmission of electric fields, (2) the flows of electric charges by means of Field Aligned Current (FAC) and (3) the precipitation and/or outflow of particles. In this work, we study some aspects of the interaction of the interplanetary coronal mass ejections (ICME) of September 6-11, 2017 event with the magnetosphere-ionosphere system. In particular, we analyze the response of the magnetosphere to the impact of the interplanetary shock preceding the ICME, the magnetospheric and the ionospheric disturbance currents, and the geomagnetically induced currents (GIC) that developed over the entire northern hemisphere.