"Recent documents from the Intergovernmental Panel on Climate Change and the UK Stern Review, have argued cogently that governments, industry and agencies should urgently address the scientific, economic and social implications of climate. The insurance industry must start adapting in response to weather and climate risks. Climate and weather forecasting hosts a wide range of scientific and mathematical methods with a heavy computational base. Insurance mathematics is a rich field, developing advanced stochastic and statistical methods within risk theory. The main objective is to bring statisticians, insurance and climate experts together to build a methodological basis for the emerging field of climate change insurance risk. Statistics is a critical part of the project. We will access insurance data from partners and agencies as well as the huge amount of actual and simulated weather and climate data. This gives us the potential to build models and methods of real relevance to decision making in the insurance industry and help inform government and regulators. Work packages include: (i) early warning of losses, (ii) interpretation of climate modelling for risk analysis, (iii) rain and wind losses, (iv) sea temperature risk (v) concurrent causes for increased loss. A range of mathematical and statistical methods will form the bedrock for the project. They include methods from probabilistic risk theory such as extreme events, methods from climate simulation, especially ensemble simulations, statistical methods such as time series and space-time models and methods from structural and system reliability. The project will attach special importance to training and dissemination. Training is critical in a multidisciplinary project as this. Dissemination is a duty imposed by the urgency of the subject and the newness of the climate change insurance risk field. Partners are in Oslo and London: Norwegian Computing Centre, London School of Economics, Lloyd’s, Gjensidige."