Heat Waves: Physical Understanding and Scientific Challenges

Heat waves (HWs) can cause large socioeconomic and environmental impacts. The observed increases in their frequency, intensity and duration are projected to continue with global warming. This review synthesizes the state of knowledge and scientific challenges. It discusses different aspects related to the definition, triggering mechanisms, observed changes and future projections of HWs, as well as emerging research lines on subseasonal forecasts and specific types of HWs. We also identify gaps that limit progress and delineate priorities for future research. Overall, the physical drivers of HWs are not well understood, partly due to difficulties in the quantification of their interactions and responses to climate change. Influential factors convey processes at different spatio-temporal scales, from global warming and the large-scale atmospheric circulation to regional and local factors in the affected area and upwind regions. Although some thermodynamic processes have been identified, there is a lack of understanding of dynamical aspects, regional forcings and feedbacks, and their future changes. This hampers the attribution of regional trends and individual events, and reduces the ability to provide accurate forecasts and regional projections. Sustained observational networks, models of diverse complexity, narrative-based methodological approaches and artificial intelligence offer new opportunities toward process-based understanding and interdisciplinary research. Plain Language Summary Heat waves (HWs) are climate extremes of major societal concern whose frequency, intensity and duration will continue increasing during this century. This review synthesizes the physical understanding and the main scientific challenges. We discuss problems involved in HW definition, including the diversity of HW indicators, and the consideration of adaptive capabilities in a changing climate. We also review observed and projected trends and the associated atmospheric patterns in different areas of the globe, with special attention to the mechanisms and drivers responsible for HW occurrence. These act at different scales, from planetary to local, and include thermodynamic and dynamical processes. There is a limited and fragmentary understanding of the interactions among these processes on regional scales, and their changes under global warming. Process-based understanding will benefit HW forecasts at time horizons longer than weather predictions, attribution of HW trends and events to human activities, and regional climate projections. Improved technological capabilities, models of diverse complexity, or machine-learning techniques will help overcome these challenges.