Climate change across scales

There is an increasing need for accurate, reliable, and actionable information, along with a deeper understanding of climate change and its physical mechanisms at global to local spatial scales, and near to long time scales.

This research area will design and implement a framework to coordinate and incorporate the suite of global and regional climate projections, promoting the collaboration between global and regional climate modelling inside and outside Rossby Centre. Joint analyses are crucial for understanding future climate change trends and extremes across these models and their underlying mechanisms. We will analyse climate processes, climate change and impacts under different global warming levels, across different spatial and temporal scales, from global to regional, and from seasonal to decadal.

A key question is how to enhance climate downscaling methods from global to regional and convection-permitting scales. It will explore the development and application of methodologies to improve the connection between global, regional, and computationally expensive convection-permitting climate models (CPMs), with a particular emphasis on downscaling techniques. By refining downscaling approaches, often using advancements in Artificial Intelligence (AI) and Machine Learning (ML), we aim to bridge the gap between large-scale climate scenarios and the specific regional/local changes they drive, enabling more precise assessments of global warming levels and their implications. Another approach is to downscale targeted events of interest (event-based downscaling). The interaction between urban and regional climate is a key area of study, as it becomes increasingly important with CPMs runs at kilometer-scale and even sub-km scale resolutions.

Objectives

The main objectives are to:

• Produce new and improved climate projections corresponding to a range of future scenarios, including scenarios matching the Paris Agreement targets and overshoot scenarios, to contribute to international efforts such as CMIP and CORDEX.
• Conduct and analyse seasonal and decadal climate prediction to provide near-future climate outlook.
• Conduct scientific analysis of climate simulations, including the assessment of global warming levels that allow assessing the impacts of climate change and evaluating mitigation pathways.
• Enhance the understanding of climate change across spatial (special focus on high resolution) and temporal scales and climate scenarios, and the underlying physical processes.
• Enhancing downscaling techniques, including the integration of AI/ML tools (such as climate model emulators), by improving methods to link global models with regional and local projections, in collaboration with other research areas.
• Coordinating our contribution to CMIP and CORDEX with more consistent and timely outcomes in support of informing the UNFCCC process and other global, European and national climate efforts.