Projections of the future changes in multiple climate hazards and resulting multiple risks to ecosystems and humans are an essential tool to enable adaptation. Yet finding the best way to combine all the available information with decision-relevant uncertainties remains an unresolved challenge. This PhD project combines climate, impacts and data science to tackle this key issue, using two complementary approaches. You would build on recent methodological developments to derive projections of climate impacts that draw on the information available in existing ensembles of climate projections. Using a Bayesian framework, you would apply observational constraints to take full advantage of the information currently available to create mode more comprehensive and defensibly climate projections. You would also look to incorporate palaeo-observational constraints under the past2future working group of PMIP4.
Policy Impact of Research:
The application of observational constraints would provide improved future forecasts.