Matt AmosPhD student, Associate Lecturer
My work uses sophisticated data science techniques to make better use of climate model ensembles, particularly focussing on atmospheric composition. We work in a field of ever-increasing model complexity, both computationally and in the physical processes they represent. Many of these models take part in inter-comparison projects which are used to inform science and policy at international levels. Despite the increase in quantity and quality of model output, many of the techniques for analysing the data have not undergone the same increase in sophistication. My aim is to better use the vast amount of information that model ensembles generate.