Environmetrics has just announced a Call for Papers for a Special Issue on Extreme Processes and Their Impact on Hazards and Risks.

Open for submission date: 1 November 2025
Submission deadline: 30 September 2026

Large-scale extreme events, such as extreme weather events, floods, and heatwaves, are expected to become more frequent and more severe due to global warming. The rapid growth of urbanization further intensifies the demand for innovative, efficient, and real-time approaches to model and predict these events. In particular, fine-resolution environmental datasets, such as those derived from climate models or satellite data products, present challenges for existing spatial extreme-value theory-based models. These traditional models are often impractical when large numbers of scenarios must be explored to understand and quantify how extreme event distributions may evolve over time.

Given this backdrop, there is a critical need for the development of new, flexible, and interpretable models, as well as efficient inference methods for spatio-temporal compound extremes. This area of research is further complicated by the increasing high-dimensional nature of the data, necessitating the integration of advanced spatial statistics and machine learning approaches to better capture the complexity and nuances of extreme events.

The goal of this Special Issue is to foster collaboration across several disciplines – including extreme-value theory, spatial statistics, scientific machine learning, and climatology – to tackle the unique challenges of modeling spatio-temporal compound extremes. We seek contributions from leading experts in these fields to develop new mathematical and statistical frameworks that can address the growing complexity of high dimensional datasets and provide more accurate and actionable predictions for extreme events. By consolidating advancements from diverse research areas, this Special Issue aims to push the boundaries of current knowledge and offer innovative solutions that can be applied in realworld scenarios, such as climate change impact studies, urban planning, and disaster risk management.

Through this Special Issue, we hope to contribute to the next generation of models and methodologies for understanding and forecasting extreme events in the face of a changing climate and increasingly complex environmental datasets.

Topics for this call for papers include but not restricted to:

• The application of machine learning methods to study extreme events
• Sparsity in models for spatial and spatio-temporal extremes
• Multivariate and graphical models for extremes
• Using climate models to project future extremes
• Detection and attribution of extreme events
• Coastal risk assessment and tropical cyclones

Applications to heatwaves, flooding, marine heatwaves, etc., or other less common environmental applications of EVT (ice sheet mass loss, etc.)

Guest Editors:

Prof. Soutir Bandyopadhyay,
Colorado School of Mines,
United States of America (the)

Prof. Richard Smith,
University of North Carolina, 
United States of America 

Prof. Raphael Huser,
King Abdullah University of Science and Technology (KAUST),
Saudi Arabia

Prof. Doug Nychka,
Colorado School of Mines,
United States of America 

Prof. Julie Bessac,
National Renewable Energy Laboratory,
United States of America