Observations suggest a clustering of severe convective storms near orography. The paper provides information on the gaps in our process understanding and the measurement techniques which are currently hampering an improved prediction of the events and their associated hazards. It provides an outline of a multinational coordinated European field campaign on Thunderstorm Intensification from Mountains to Plains.

I would like to support the proposal by the reviewer and the handling editor. This innovative study reconstructs the precursory phenomena of the 1538 Campi Flegrei eruption using historical records and recent volcanological data to develop two alternative scenarios that inform civil protection strategies for managing current unrest and potential eruptions in the densely populated area.

This paper systematically reviews 250 studies (2010–2023) on the use of social media data (SMD) in disaster management, highlighting its applications in relevance filtering, actionable information extraction, and decision-making enhancement. It develops a comprehensive literature database and identifies key trends, advantages, and challenges, proposing best practices for leveraging SMD to improve disaster response, communication, and management strategies.

The study draws on a unique dataset collected from a survey of nearly 500 water managers engaged in addressing the 2022 European Drought. It offers valuable insights into how preparedness influences outcomes during large-scale drought events and highlights pathways to strengthen European Drought Risk Management. The manuscript is accompanied by a companion paper, "The 2022 Drought Needs to Be a Turning Point for European Drought Risk Management" (egusphere-2024-2069), which focuses on the drought’s impacts and response. Together, the two studies underscore the urgent need for coordinated action and conclude with policy recommendations for establishing a European Union Drought Directive

This study uses insurance loss data to examine how different types of extreme weather—such as floods, heavy rain, windstorms, and hail—occur together. It finds that multiple hazards often cluster seasonally, leading to higher losses than when events happen alone. The results highlight the need to assess multiple weather extremes jointly to better understand and manage risk.

This study presents the first end-to-end Earthquake Early Warning system designed specifically for Italy’s high-speed railway. It details the full implementation process, demonstrating the technical and operational complexities of integrating real-time seismic alerts with rigid railway control interfaces capable of triggering automatic emergency braking. The successful pilot application has led the Italian railway company (Rete Ferroviaria Italiana, RFI) to prepare for expansion of this system to additional high-speed rail segments across the national network.

This study provides new insights into hailstorm diagnosis from future European climate simulations.

This paper addresses an important research question for the region of interest in the special issue, "Current and future water-related risks in the Berlin-Brandenburg region." The article analyzes groundwater trends using a rigorous methodology that takes into account all factors that could justify the results found. It is therefore highly relevant for water resource management, which is particularly affected by climate change.

The study investigates the potential of cloud seeding to mitigate extreme rainfall localization associated with mesoscale convective systems. Using a numerical weather prediction model, numerical cloud seeding experiments were conducted artificially increasing ice nuclei concentrations in a double-moment microphysics scheme for the heavy rainfall event. For a disastrous event that occurred in Japan in 2014, the authors show that idealized overseeding can suppress peak rainfall in high risk areas while producing an accompanying rainfall increase downwind. Estimates of the required amount of seeding substances in practical applications are provided.