Increasingly, computer-based simulations are being used to make actionable predictions, whether that be for drug design, climate modelling, or diagnosis of disease. This theme issue addresses the question “are the methods used today sufficiently reliable to generate actionable results?”, based on three notions of reliability: validation, verification, and uncertainty quantification.

This theme issue summarises recent advancement in our understanding of widespread topics of dynamic fracture. Spatiotemporally multiscale subjects range from fracture of bi-metal interface at particle levels, to disastrous rock bursts in deep gold mines, and detection of unique signals before devastating fracture such as large, globe-scale earthquakes.

The need to decarbonise energy systems gives rise to many challenging areas of interdisciplinary research, bringing together mathematicians, physicists, engineers, and economists.

The recent rise of machine learning begs the question of how these tools can help improve weather and climate forecasting. In this theme issue, experts from weather and climate modelling and machine learning highlight and address the exciting challenges found across a wide range of problems within this field.