Climate extremes and attribution

Global temperature increases and the frequency and intensity of extreme events are trending toward the upper limits of previous model projections. While natural variability may play a role, potential amplifying effects within the Earth system must be considered. Understanding, detecting, and attributing the causes of climate extremes is therefore very important.

This research area focuses on analyzing and identifying the mechanisms underlying extreme weather and climate events, spanning different spatial and temporal scales. By analyzing the driving factors behind phenomena such as heatwaves, heavy rainfall, and droughts, this research contributes to distinguish the relative contributions of natural variability and anthropogenic climate change to the occurrence of such events.

Improving the predictability of extreme events is essential to better prepare for their societal and economic impacts. This requires investigating the extent to which different types of climate extremes can be forecasted at various temporal and spatial scales. Additionally, changes in climate modes of variability, such as the El Niño-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Arctic Oscillation (AO), may influence the timing, intensity, and location of extreme events. Understanding how these large-scale climate patterns interact with climate change is crucial for anticipating future extremes, improving early warning systems and plan for climate adaptation.

Objectives

The objective of this research area is to enhance our understanding, detection, and attribution of climate extremes across spatial and temporal scales by:

• Investigating the physical processes and interactions leading to extreme events.
• Investigating the predictability of climate extremes at different temporal and spatial scales.
• Researching how changes in climate variability, including changes in climate modes of variability, drive changes in extreme events.
• Contributing to the development and implementation of methods for detecting and analyzing climate extremes, such as machine learning. in coordination with the other research areas.
• Advancing the concept of climate extreme attribution.
• Providing insights into how extreme events are expected to evolve in the future.

This research area will also explore the current state of the art of attribution to climate change studies, aiming to establish links with researchers within the Nordic countries and Europe focused on attribution studies.