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Attend this seminar presentation by Professor Tamsin Edwards from King's College London exploring methods for quantifying uncertainties in multi-model, multi-input ensembles of ice sheet and glacier change. Learn about statistical approaches to understanding and representing prediction uncertainty in climate modeling, specifically focusing on ice dynamics and glacial systems. Discover how multiple models and input parameters can be combined to better assess uncertainty ranges in projections of ice sheet behavior and glacier evolution. Examine the challenges of calibrating complex ensemble models and leveraging uncertainty quantification techniques that bridge traditional statistics and modern machine learning approaches. Gain insights into the mathematical and computational methods used to represent confidence intervals and uncertainty bounds in climate science predictions. Explore practical applications of these uncertainty quantification techniques for improving climate projections and informing policy decisions related to sea level rise and glacial change.
