82 episodes

Our best estimates of future climate are based on the use of complex computer models that do not explicitly resolve the wide variety of spatio-temporal scales making up Earth's climate system. The non-linearity of the governing physical processes allows energy transfer between different scales, and many aspects of this complex behaviour can be represented by stochastic models. However, the theoretical basis for so doing is far from complete. Many uncertainties remain in predictions derived from climate models, yet governments are increasingly reliant on model predictions to inform mitigation and adaptation strategies. An overarching aim of climate scientists is to reduce the uncertainty in climate predictions and produce credible assessments of model accuracy. This programme focuses on two key themes that both require the close collaboration of mathematicians, statisticians and climate scientists in order to improve climate models and the interpretation of their output.

Read more at http://www.newton.ac.uk/programmes/CLP/index.html

Mathematical and Statistical Approaches to Climate Modelling and Prediction Cambridge University

    • Science
    • 4.0 • 3 Ratings

Our best estimates of future climate are based on the use of complex computer models that do not explicitly resolve the wide variety of spatio-temporal scales making up Earth's climate system. The non-linearity of the governing physical processes allows energy transfer between different scales, and many aspects of this complex behaviour can be represented by stochastic models. However, the theoretical basis for so doing is far from complete. Many uncertainties remain in predictions derived from climate models, yet governments are increasingly reliant on model predictions to inform mitigation and adaptation strategies. An overarching aim of climate scientists is to reduce the uncertainty in climate predictions and produce credible assessments of model accuracy. This programme focuses on two key themes that both require the close collaboration of mathematicians, statisticians and climate scientists in order to improve climate models and the interpretation of their output.

Read more at http://www.newton.ac.uk/programmes/CLP/index.html

    • video
    Climate Change Question Time: The scientific uncertainties and their implications

    Climate Change Question Time: The scientific uncertainties and their implications

    Climate Change Question Time: Panel Discussion
    Wednesday 24 November 2010, 14:30-16:00

    • 1 hr 30 min
    • video
    Statistical processing for ensembles of numerical weather prediction model

    Statistical processing for ensembles of numerical weather prediction model

    Gneiting, T (Heidelberg)
    Tuesday 21 December 2010, 10:00-11:00

    • 1 hr 11 min
    • video
    Climate Change Question Time: Estimating and reducing uncertainty in climate prediction: key findings from the Newton Institute Programme

    Climate Change Question Time: Estimating and reducing uncertainty in climate prediction: key findings from the Newton Institute Programme

    Tim Palmer (University of Oxford, and the European Centre for Medium-Range Weather Forecasts)
    Wednesday 24 November 2010, 14:05-14:30

    • 36 min
    • video
    Climate Change Question Time: Policy in the face of the uncertainties

    Climate Change Question Time: Policy in the face of the uncertainties

    Climate Change Question Time: Panel Discussion
    Wednesday 24 November 2010, 16:30-18:00

    • 1 hr 31 min
    • video
    Climate Investments optimized under uncertainty

    Climate Investments optimized under uncertainty

    Held, H (PIK)
    Thursday 09 December 2010, 16:10-17:00

    • 52 min
    • video
    Engagement with business- What are the barriers to use of climate data, where should future research be taken?

    Engagement with business- What are the barriers to use of climate data, where should future research be taken?

    Whitaker, D (Knowledge Transfer Network)
    Thursday 09 December 2010, 15:30-16:10

    • 43 min

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