The Arctic is warming rapidly. We observe that the sea ice is retreating, and the melting of the Greenland ice sheet is accelerating. This project will use mathematical and statistical models to investigate if the warming will lead to abrupt changes in the climate, affecting ecosystems and societies. The level of warming where such transitions occur are refered to as tipping points in the climate system, and our goal is to assess the associated risk.
Since the last ice age, arctic climate has been very stable, but during the ice age, climate in the Arctic was characterized by repeated rapid warming and cooling events. The complex Earth system models, however, do not reproduce these rapid changes very well and may not be able to predict loss of stability of the Arctic climate under continued global warming. An alternative can be to use simple, conceptual models that describe specific processes that can lead to accelerated change. On the other hand, these simple models may disregard important balancing effects and exaggerate the risk of abrupt climate change.
Thus, both simple and complex models have limitations and weaknesses, which calls for adopting a wide range of models and methods. Our approach is to use conceptual models that are constructed and calibrated using both observational data and experiments in complex Earth system models. In the complex models, we can set up experiments specifically designed to determine which processes we need to include in the simple models. Using statistical methods, we will tune the simple models to observations and simulated climate data from complex models before using them to answer questions about the stability of the Arctic climate.
The Arctic is experiencing stronger warming than the planet as a whole and the amplification is predicted to become even stronger over the next century. Even if the Paris Agreement goals are met Arctic winter temperatures can increase by several degrees by 2050. The Arctic sea-ice cover is retreating and the Greenland ice sheet is rapidly melting. Fresh meltwater from the Greenland ice sheet is slowing down the upper cell of the Atlantic meridional overturning circulation. These coupled non-linear processes make the Arctic climate potentially unstable under further greenhouse warming. Indeed, paleoclimatic reconstructions show evidence of events of abrupt climate change such as the Dansgaard-Oeschger events in Greenland during the last glaciation. These abrupt transitions are largely missing in state-of-the-art complex climate models and structural model errors have been argued to be the main reason. This calls into question whether they can be expected to reliably estimate the stability of the Arctic climate under the recent global warming. In contrast to complex climate models, simplified models can exaggerate non-linear effects. A well-known example is the sea-ice albedo feedback, which in simple energy-balance models gives rise to instability of a small ice cap. This instability is not seen in more complex models. This project will combine conceptual, physics-based dynamical system models of Arctic climate response with data-driven approaches and paleoclimatic data. Conceptual models will be calibrated against the complex climate models in the climate regimes where we have confidence in the complex models. For this purpose, we will design and carry out a modelling study, which includes sets of experiments in a particular complex model that explores differences in the Arctic climate response for different background states under suppression of selected feedbacks.