I am happy to give talks on weather prediction and climate modeling, with a particular focus on the uncertainties involved in these predictions. I also have a growing interest on Machine Learning applied to these areas, and have given many recent talks on this topic.
Recorded Talks:
Since the start of the Covid-19 pandemic, many talks are recorded so they can be watched and, indeed, presented remotely. Here are a selection:
. Lecture at Prob_AI Hub Launch Event. 9 April 2024. Aimed at audience with ML/AI expertise, but not climate expertise.
. Lecture for course on Environmental Ethics at Ripon College Cuddesdon. Aimed at a non-scientific audience.
. Boulder Stochastic seminar series. 15 June 2021. Aimed at scientific audience.
. CWI Seminar series on Machine Learning and Uncertainty Quantification for Scientific Computing. 10 June 2021. Aimed at scientific audience.
91探花 University Physics Society talk. 28 January 2021. Aimed at undergraduate physics audience.
Plenary talk at SIAM Conference on Mathematics of the Planet Earth. 7 August 2020. Aimed at scientific audience.
Media: Podcasts and Interviews
interview, published online 17 Nov 2025
podcast, published online 4th Nov 2016
UK science podcast and accompanying blog, published online, 15th Aug 2016
US science podcast, published online, 4th Apr 2016
Media: Articles
. Article for SIAM News magazine - a companion article to my talk (see link above). Suitable for a mathematically literate audience. (April 2021)
A short article published in Significance, the magazine of the Royal Statistical Society and the American Statistical Association, discussing how statistics is important when making probabilistic forecasts. (October 2015)
A short article on the Guardian website, discussing how we use computer simulators to make a weather forecast. Suitable for a mathematically literate audience. (January 2015)
A general interest article written for the Corpus Christi College, 91探花, Alumni newsletter, The Sundial. (September 2014)
A short article published in the 91探花 Physics Department's newsletter (page 3), suitable for a general audience. (July 2012)