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Synthesising Model Projections of Future Climate Change

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If you have a question about this talk, please contact Mustapha Amrani.

Mathematical and Statistical Approaches to Climate Modelling and Prediction

It has never been a more exciting time to be a climate modeler. International coordination of model experiments by the Coupled Model Intercomparison Project (CMIP5) will see the estimated production of over 2 petabytes of model output from 20 modeling centers and 40 different climate models (downloading the data on a home broadband would take 25 years). There will be new model functionality in terms of the processes represented in the models including chemistry and biology, new forcing scenarios including palaeoclimate and idealized cases and new experiments initialized with observations to look at near-term climate variability and change. Moreover there is an unprecedented interest in, and scrutiny of, climate model projections from fellow scientists, from the public and from governments.

How on earth are we to make sense of this information overload? This talk will review some of the approaches that we expect will be used to analyses the new CMIP5 multi-model database. Some approaches rely on physical understanding of the climate system to make sense of the data. Some use simple statistical approaches to rationalize the output. In some specific cases, more complex statistical approaches may be applied carefully. Finally, all the approaches will have to be synthesized to provide a summary of the state of climate modeling science. This challenge will be discussed.

This talk is part of the Isaac Newton Institute Seminar Series series.

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