The interactions of a turbulent wind with a water surface represents a very fundamental problem for many atmospheric processes.
The momentum and heat exchanges across the interface with oceans abruptly affects the atmosphere and the understanding of the driving mechanisms would certainly improve weather predictions capabilities. However, after decades of research efforts, the wind-wave problem is still recognized as extremely elusive. The reason is the multiscale and multiphysical nature of the phenomena involved. Indeed, the scales of the turbulent wind are significantly affected by the smaller scales of the water waves which in turn are influenced by the structure of the turbulent wind itself thus forming a complex multiscale coupling phenomenon. Furthermore,
processes of different nature are involved (e.g chemistry, biology, radiation etc) thus further increasing the complexity of the multiscale wind-wave interactions due to multiphysics. The SEAPLANE project aims to address these issues by using innovative statistical tools and advanced modeling approaches.

Hydrological extremes are strongly impacted by climate change and represent one of the most relevant and hard-to-predict hazards over the Italian territory. The evaluation of the effectiveness of adaptation actions for water-related hazards requires actionable information about climate change and future hazards. Current methodologies based on multi-model downscaled climate projections are challenged by high uncertainty and large model bias. To deal with such uncertainty, event-based storylines have been proposed as a complementary approach that is much more tailored around stakeholders' needs. The storylines describe plausible unfolding of extreme events, based on realistic simulations and an end-to-end description linking physical drivers to regional impacts. In this direction, recently developed weather and climate predictions provide unprecedented high-resolution large-ensemble numerical simulations to develop large catalogues of extreme events that can complement the short observational series and support storylines via the identification of unseen weather extremes.

How does climate change impact extreme events and which is the future change of their dynamics? In other words: How will the ongoing and future changing climate control the evolution and intensification of severe storms? These are among the most frequent and significant questions for the scientific community, stakeholders and decision-making structures. The project tackles these open issues by investigating hailstorms in the Mediterranean region, which is one of the most hail-exposed areas of the Earth, through the
synergistic application of satellite observations, meteorological reanalysis and climatic modelling. Focussing on determining the atmospheric variables most relevant for the formation and intensification of hail-bearing storms, we will delineate specific metrics describing the hail formation potentially applicable at operational level. The proposal stems from the 22-yearlong database of hail episodes described by Laviola et al. (2022), whereby events associated with large and extreme hail (above 2 and 10 cm in diameter, respectively) were preliminarily identified and shown to be on a 30% increase trend.

Nowadays, effective procedures for the assessment of the stability conditions of rock cliffs and the associated retreat rates is of increasing relevance for the institutions devoted to land management. These phenomena result from a complex interaction between the meteo-marine controlling factors and the geo-structural and geo-mechanical conditions of the rock mass, so that the phenomenological and qualitative approaches, used in the past to deal with this problem, have resulted to be ineffective and inadequate. This research project is aimed at developing a multi-scale quantitative methodology to deal with the prediction of rock cliff retreat phenomena, with the following objectives:
1) large-scale assessment of the retreat rates of rock cliff coastlines highly susceptible to instability phenomena by means of advanced geomorphological techniques and detection of the main driving factors at regional scale;
2) analysis of the sea-air-cliff interaction processes, focusing specifically on the assessment of the extreme wave events and important environmental factors acting on the rock cliffs, as the sea spray;
3) development of a slope-scale methodological procedure for the integration

The goal of the NEW-ARGENT (NumErical Weather prediction improvement through the Assimilation of Real-time Gnss Estimated Non-isotropic Troposphere, all acronyms are in section B1.4) project is to improve the short-term (from 30 minutes to 12 h) prediction of convective and severe weather events over Italy through the GNSS (GPS, Galileo, Glonass and Beidou) tropospheric delays assimilation and to design an overall procedure and raise it at a pre-operational stage.
NEW-ARGENT finds its motivation in the following considerations.
It is well known since some decades ago that GNSS can supply information about the water vapor content in the troposphere, and this result is routinely got in high-precision GNSS data processing for geodetic and geophysical monitoring purposes in order to mitigate as much as possible the effect of the troposphere onto the positions of points on the Earth surface. Also, it has already been prediction. Anyway, the adopted models and procedures are oriented to get the best positions, generally on a daily basis, and not the best estimates of the water vapor content in the troposphere to routinely improve weather predictions.

Climate models project an overall aridification of the Mediterranean environment at the end of the 21st century, mostly linked to the expansion of the subtropical edge of the Hadley circulation. During the transition towards a subtropicalised mean climate state, the characteristics of extreme events will change. Prolonged droughts (months-to-years), such as the one observed in 2022 over Italy and Europe, are expected to become more frequent (5 to 10 times more than recent past) and severe at the end of the 21st century.
Previous studies on future Mediterranean climate mostly focused on long-term mean changes. Furthermore, past analyses of Mediterranean droughts and extremes have been limited by availability of sufficient observational and model datasets to perform rigorous detection and attribution analysis. Instead, DROMEDAR will rely on large ensembles, a definitive tool for the study of extreme events, because they allow us to explore climate signals beyond the influence of the internal variability.

Fine atmospheric particulate matter (PM2.5) is a major risk for public health, potentially leading to millions of premature deaths per year worldwide. The mechanisms and factors inducing PM2.5 toxicity are still not fully known and contrasting results are obtained when different acellular and cellular in vitro toxicity metrics are compared among themselves or with in vivo toxicity. This leads to major issues in air quality studies and pollution mitigation strategies: the detailed knowledge of the impact of PM2.5 sources on
health effects; the most performant metrics to represent toxicity, especially in urban areas where there are combined effects of several anthropogenic sources.
The aim of the TOX-IN-AIR project is threefold:
1) Investigate how acellular and intracellular toxicity indicators correlate one among the other and with the total and water soluble chemical composition putting in evidence seasonal and site dependencies.
2) Evaluate the contributions of the different natural and anthropogenic sources to the toxicological indicators and the nonlinear interactions among the sources and the toxicity metrics.
3) Develop new combined metrics to better represent the global...

Groundwater plays a key role in addressing global water needs. Around 20% of the world's aquifers are over-exploited, with outputs (withdrawal and natural discharge) exceeding recharge, resulting in resource depletion, storage loss in sandy layers and compaction of confining clay beds. The induced land subsidence causes direct/indirect impacts on urban landscapes (ground depressions, earth fissures, structure damages, increased flood risk, loss of land to water bodies) and economic loss, yet these are often overlooked, and so are considerations on how climate change, population and urban growth may further exacerbate them.
SubRISK+ will innovate in this field by providing new EO-derived products and tools aiming to: 1) enhance our understanding of subsidence and its impact; 2) empower the community to recognize the human-related  behavioral, socio-economic and demographic drivers of this geohazard and its cascading effects on urban environments and ecosystems; and 3) strengthen our ability to use consciously natural resources to make a step-change towards sustainable development.

Fire is an important ecosystem disturbance, having significant socio-economic consequences on the one hand, while fulfilling a vital ecological role on the other. Across fire-prone ecosystems, different fire regimes can be found, reflecting a combination of climatic factors and of different plant species characteristics. Ecosystem flammability and fuel load are the most evident and well-studied aspects of plant interactions with fire regimes. Only recently, has there been a major focus on how other plant traits, and especially fire responses, shape the fire regime. For example, invasive alien species with highly competitive traits, when introduced by humans into novel ranges, can have dramatic impact on the local fire regimes. The aim of this research is to determine the role that plant traits have in driving fire regimes in different ecosystems across the world and for various climates, including also the role played by invasive species.