Climate change research is associated with various kinds of uncertainty. Some are inherent (e.g. unpredictability from non-linearity of the governing physics), some reflect lack of computing power or precise knowledge (e.g. cloud processes). Some of the uncertainties can be unravelled using systematic sampling and exploration. The field of statistical climatology, placed on the interface between statistics and climate science, deals intimately with these uncertainty issues, including climate change detection (hypothesis testing from a statistical point of view), model and parameter uncertainty, trend estimation, space-time-frequency decompositions, etc.

Statistical climatology can focus climate impact and adaptation efforts by providing decision makers descriptions of the future that include uncertainty. This complements climate science, with its complex models and huge data sets. Indeed, research training on these topics is relatively unexplored. There is a strong need for cross-disciplinary training in this intersection between climate science and statistics.

This Nordic network, funded by Nordforsk, aims at building capacity for this type of training, through activities such as workshops, student exchange, and collaborative research involving both statistician and climate scientists. Because the different academic groups involved in this project have limited personnel, the proposed network structure offers a way of creating a critical mass of researchers working on these problems, and collaborating not only across disciplinary boundaries, but also across university and national boundaries, including meteorological institutes, where scientists are routinely struggling with the types of questions addressed in this project.