Nazario Tartaglione

Fire has acted as a major eco-evolutionary force since the evolutionary appearance of plants, shaping plant-traits, diversity, vegetation assembly, and ecosystem functioning. Its ecological role depends on long-term fire regimes. Anthropogenic land-use change and climate warming are disrupting these regimes, particularly in densely populated regions such as the Mediterranean Basin. In the Italian peninsula (Mediterranean region) fire activity peaks during the dry summer months and is projected to intensify under climate change scenarios. Recent methodological developments – based on emerging satellite data, ground-based observations combined with Random Forest (RF) habitat classification, and spectral indices such as the NDVI provide a robust framework for monitoring post-fire land-cover dynamics over time. In this study, we applied RF modelling to classify vegetation cover using a 2017–2024 satellite imagery time series of the Monte Pisano area (central Italy) to assess pre- and post-fire vegetation trajectories. Evergreen shrubs and trees exhibited rapid post-fire regrowth, whereas coniferous stands showed slower recovery rates. NDVI trends revealed an expected sharp decline immediately after the fire, followed by gradual recovery of broadleaf forests and shrubland communities. Moreover, our results indicated a progressive increase in the cover of native deciduous and evergreen species of high conservation value (listed under the Habitat Directive). The framework delivers spatially explicit insights into post-fire recovery, supporting targeted management, restoration under European Nature Restoration Regulation, and long-term monitoring in Mediterranean ecosystems. Incorporating fine-scale environmental variables may further improve classification accuracy and enhance assessments of vegetation resilience and ecosystem recovery following fire events. Highlights: Recurring fires strongly affect ecosystem structure and function in Mediterranean landscapes. Integrating remote sensing with Random Forest models enables effective monitoring of post-fire vegetation recovery over time. NDVI time series provide reliable proxies for tracking vegetation vigor and land-cover change. Post-fire recovery trajectories are shaped by fire severity, vegetation physiognomy, plant functional types, and soil conditions. Targeted restoration and management interventions informed by spatial–temporal vegetation patterns are urgently needed. The proposed framework aligns with objectives of the EU Nature Restoration Regulation for ecosystem and habitat recovery.

This study investigates whether, when using multispectral imagery, it is preferable to retrain a random forest model once a year or to train it for a single year and then use that model to predict all subsequent years. We utilized Sentinel-2 images as the primary input features along with environmental data for the study. The targets representing both natural and semi-natural habitats for classification were used in an area of central Italy. By excluding all burned areas since 2001, we assessed the area’s stability over the past nine years. The approach involved conducting a twin experiment to compare the results of model training and predictions under two distinct scenarios. In the initial experiment, named SINGLE, the model was trained using data from one year (2023) and subsequently applied to generate land cover maps spanning from 2016 to 2024. In the second experiment, known as MULTI, the model undergoes annual retraining before forecasting the land cover for each respective year. The findings reveal that in the MULTI experiment, the accuracies are not only superior to those in the SINGLE experiment but also exhibit consistent stability, highlighting the effectiveness of annual model retraining.

On 15 September 2022, a flood affected the Marche region, an Italian region that faces the Adriatic Sea. Unlike previous floods that affected the same area, no typical weather system, such as cyclones or synoptic fronts, caused the recorded extreme precipitation. In fact, the synoptic situation was characterized by a zonal flow, which normally does not cause intense precipitation over that area. The aim of this study was to understand which ingredients led to extraordinary precipitation in the region. ERA5 and the Weather Research Forecast (WRF) model were used to describe the synoptic situation and to reproduce rainfall. While limited area models with a horizontal resolution of a few km failed to forecast the precipitation, as confirmed by a WRF simulation with a horizontal resolution of 3 km, reducing the horizontal grid spacing to about 500 m improved the rain’s reproducibility. Together with a zonal flow that interested most of Italy, an atmospheric river starting in the eastern Mediterranean Sea transported moisture over the region. The interaction between the zonal flow and orography resulted in frontogenesis in the Apennine Lee. This process deformed the thermal structures in the area and created conditions of convective instability, transforming the moisture into copious rainfall. Moreover, ERA5 and the time series of observed rainfall from 1959 to 2022 were used to explore whether similar events, in terms of geopotential height configuration and rainfall, occurred in the past. Three metrics were employed to compare the event’s 700 hPa geopotential height pattern with all the other patterns, and the result was that the event was unique in the sense that a zonal flow, like that observed during the event of 15 September 2022, had never produced such an amount of precipitation in the time range considered, while all the events with the highest rainfall were usually associated with cyclonic structures.

Aerosols significantly affect cloud microphysics and energy budget in different ways. The contribution of the direct, semi‐direct, and indirect effects of aerosols on radiation are here investigated over the North Atlantic tropical ocean under different aerosol loadings. The Weather Research and Forecasting Model is used to perform a set of numerical idealized experiments, which are forced with prescribed aerosol profiles. We evaluate the effects of aerosols on modeled shallow clouds and surface radiative budget. The results indicate that large aerosol loadings are associated with enhanced cloudiness and reduced precipitation. While the change in rainfall is mainly due to the larger number of smaller droplets, the change in cloudiness is attributed to the effects of absorbing aerosols, mainly dust particles, which are responsible for a rise of temperature that feeds back onto specific humidity. As in the boundary layer the increase of moisture dominates, the net effect is a higher relative humidity, which favors the formation of thin low non‐precipitating clouds. The feedback accounts for a dynamical change in the lower troposphere: shortwave radiation absorption increases temperature at the top of the marine atmospheric boundary‐layer and reduces entrainment of warm and dry air, increasing low level moisture content. Despite the overall increase in cloudiness, daytime cloud cover is reduced. The semi‐direct effect of aerosols on clouds results in a warming of the surface, opposite to the indirect effect.

Observational studies suggest that part of the North Atlantic Oscillation (NAO) variability may be attributed to the spectral ultra-violet (UV) irradiance variations associated to the 11-year solar cycle. The observed maximum surface pressure response in the North Atlantic occurs 2–4 years after solar maximum, and some model studies have identified that atmosphere–ocean feedbacks explain the multi-year lag. Alternatively, medium-to-high energy electron (MEE) precipitation, which peaks in the declining phase of the solar cycle, has been suggested as a potential cause of this lag. We use a coupled (ocean–atmosphere) climate prediction model and a state-of-the-art MEE forcing to explore the respective roles of irradiance and MEE precipitation on the NAO variability. Three decadal ensemble experiments were conducted over solar cycle 23 in an idealized setting. We found a weak ensemble-mean positive NAO response to the irradiance. The simulated signal-to-noise ratio remained very small, indicating the predominance of internal NAO variability. The lack of multi-annual lag in the NAO response was likely due to lagged solar signals imprinted in temperatures below the oceanic mixed-layer re-emerging equatorward of the oceanic frontal zones, which anchor ocean–atmosphere feedbacks. While there is a clear, yet weak, signature from UV irradiance in the atmosphere and upper ocean over the North Atlantic, enhanced MEE precipitation on the other hand does not lead to any systematic changes in the stratospheric circulation, despite its marked chemical signatures.

Interannual changes in spectral irradiance at UV wavelengths is one of sources of solar-driven decadal variability in the atmosphere and in particular in the stratosphere as most of these changes happen at UV wavelengths. In last recent years, it has been suggested that energetic electron precipitation (EEP) also contributes not only to alter the chemical composition of the middle atmosphere but also its dynamical variability through changes in stratospheric ozone. In this study we investigate the effects of the two forcings and their interactions. We employ 35-year long integrations of the atmospheric version of the Whole Atmosphere Community Climate Model version 5 with different idealized and stationary solar and geomagnetic forcing terms. Four experiments are carried out combining high (H) and low (L) solar radiative forcing and high (7) and low (3) EEP associated with geomagnetic activity: H7 (with high radiative forcing and high EEP), H3 (high/low), L7 (low/high), and L3 (low/low). We find that the extension, the seasonality, and the significance of the effects of these two forcing terms on the atmospheric variables like temperature, NOx, and ozone are dependent on the joint effects of both forcing terms. The effect of the impact on NOx, ozone and temperature was measured, on constant pressure levels, by means of a Monte Carlo test. Under minimum solar conditions EEP affects mainly the NOx field on constant pressure levels, even though vertical cross sections show statistically significant effects on temperature and ozone in the southern hemisphere during austral winter and the following spring. Under solar maximum condition the effect of EEP becomes important. Ozone depletion (augmentation) in the upper levels of the stratosphere due to more (less) NOx, produced by EEP, allows UV radiation to produce more (less) ozone in the lower levels of the stratosphere. Solar irradiance hence plays an important role in modulating the impact of geomagnetic activity on climate variables.