Centre for Statistics

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:

 

Unfortunately, registration for the event is now full. 

Organised by Gabi Hegerl, Nicole Augustin and Amanda Lenzi.

Dec 06 2022 -

Modelling extremes and causal inference in the context of geoscience and climate change data.

The Centre for Statistics is hosting a Research Day on modelling climate change data organised in collaboration with the School of Geosciences.

JCMB 5327