Can we quantify uncertainties in complex models of the complete Earth System?

The models we are using to base our judgements on are all imperfect. We must acknowledge this and attempt to address quantitatively how these uncertainties affect the judgements we are able to make on the basis of these models. Without uncertainty estimates (error bars if you like) any decision making will be arbitrary. With them it is more complex, remains subjective but at least can be justified and explained. This will be essential if the hard choices that we face are to be effectively communicated and acted on. Addressing uncertainty is central to all aspects of modelling, from the dynamic climate models to models of ecological systems, society and economics. Coupling such models makes uncertainty quantification even more essential. I believe this is a fundamental question to address before we can even start to answer specific questions about the Earth System.

How to deal with the uncertainties associated with Earth system research, especially policy-relevant areas?

In addition to climate change uncertainties, we are still lack of knowledge about interactions of land-atmosphere, Atmosphere-sea, aerosol-climate, chemistry-climate, and more importantly human-environment relationships.

What are the regional expressions of climate change?

Over the last decades and years, the question of climate change attribution has been resolved scientifically and we have made good progress in constraining the magnitude of greenhouse warming at a global scale. In contrast, the regional expression of climate change is still poorly understood, hence providing a vague physical basis for foresighted political decisions and socioeconomic planning.

Gaps to fill in our knowledge on regional climate relate to regional trends and magnitudes of monsoon precipitation, drought in subtropical regions of both hemispheres, Arctic warming (including melt of sea ice and Greenland ice), prevalent climate modes and seasonality in mid-latitude regions, etc.

Focused research over the next decade should be able to constrain many of the uncertainties about the regionally relevant aspects of climate change. Such research needs to address regional climate dynamics across past and present timescales, based on targeted, high-resolution climate modeling and the generation and analysis of detailed paleo-climate reconstructions and climate-observation datasets. Without better-founded expectations about regional changes, any research on global change impacts and adaptation measures will be built on sand and remain speculative.

How can we improve societal learning in dealing with complex challenges?

A unifying feature of all environmental and sustainability challenges is the complexity and uncertainty of the issues and relationships between goals, and problems. In order to deal effectvely with these issues we need to better learn about the interconections, and develop new approaches to policy making that reflect these lessons. Many tentative efforts have already been made in this direction.

Obstacles have to do with how communities of knowledge are organized and funded, and the possible trade offs between relying on technical expertise and democratic values. While they are not fundamental opposites, their potential contradictions do need to be considered and addressed.