Modelling extremes and causal inference in the context of geoscience and climate change data
Modelling extremes and causal inference in the context of geoscience and climate change data.
The idea is to bring together geoscientists and statisticians. Geoscientists working on interesting problems to do with Climate Change where more statistical input might be useful. Statisticians working on methodology which could be useful for above geoscientists (extreme value theory, causality, data assimilation, Bayesian Statistics, spatio(-temporal) modelling, time series). Initially we will concentrate extreme events and causal inference/event attribution.
Schedule
11:00-11:05 Welcome from Nicole Augustin
11:05-11:25 Sjoerd Beentjes (School of Mathematics)
11:25-11:45 Simon Tett (School of Geosciences)
11:45-12:05 Emiko Dupont (Department of Mathematical Sciences, University of Bath)
12:05-12:45 Speed Talks
12:45-13:45 Lunch
13:45-14:25 Speed Talks
14:20-14:40 Andrew Schurer (School of Geosciences)
14:40-15:00 Ioannis Papastathopoulos (School of Mathematics)
15:00-15:20 Mark Naylor (School of Geosciences)
15:20-17:00 Breakout discussion groups and coffee
Download the full program, which includes titles and abstracts:
Organised by Gabi Hegerl, Nicole Augustin and Amanda Lenzi.
Modelling extremes and causal inference in the context of geoscience and climate change data
JCMB 5327