Workshop on Model Uncertainty for Weather and Climate Prediction, University of Oxford, 23-26 September 2024

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Laura Anne Mansfield

Jun 12, 2024, 12:14:40 PMJun 12
to Climate Informatics News

Dear Colleagues,


Apologies for cross-posting.


We are delighted to announce an upcoming workshop on Model Uncertainty for Weather and Climate Prediction, to be held in the Department of Physics, University of Oxford, 23-26 September 2024 


All those interested in attending must complete the registration form on our website. If you are interested in giving a talk or poster presentation, you can also submit your abstract using the same form. Please register your interest and submit abstracts by 23 June 2024.


There will be no abstract submission fee or attendance fee. Lunch and refreshments will be provided for confirmed participants free of charge, as well as a conference dinner on the Tuesday night. We gratefully acknowledge funds from the UK Natural Environment Research Council and the Leverhulme Trust to support this event.


A synopsis can be found below.




Future predictions of the Earth system are uncertain, whether spanning a few days or many decades. A key source of uncertainty across all these timescales are the approximations made when building the Earth System Model used to make the prediction. This is called model uncertainty.


This workshop will bring together different communities interested in model uncertainty, including but not limited to: those working on weather prediction through climate timescales; those focused on physical parametrisations, the dynamical core, or their coupling and interaction; those using high-resolution km-scale models through complex Earth System Models; whether limited area or global.


We welcome papers on quantifying, understanding and/or representing model errors and model uncertainty, including through multi-model ensembles, parameter perturbation experiments, or stochastic approaches, among others. Statistical approaches including machine learning are also of interest.


Confirmed invited speakers include


V. Balaji (Princeton/Schmidt Sciences)

Ben Booth (UK Met Office)

Christoph Schär (ETH Zurich)

Antje Weisheimer (ECMWF/ U Oxford)

Matthew Willson (Google DeepMind)


Key workshop themes

•     Representing model uncertainty including the use of ensembles; stochastic parametrisations; multi-model and perturbed parameter approaches; model error and uncertainty in data assimilation

•     Understanding and quantifying model error; observational constraints;

•     Model uncertainty across model hierarchies, across temporal scales, and across spatial scales; the use of unified or seamless approaches to improve and constrain predictions;

•     Resolution issue: the development of scale-aware parametrisation schemes; parametrisation across the grey-zone; km-scale modelling;

•     The role and use of machine learning (ML) in all the above; model uncertainty in an ML context




We hope to see many of you there! Please do not hesitate to get in touch by emailing if you have any questions. Please also feel free to forward this announcement to interested colleagues.


Best wishes,

Laura Mansfield




On behalf of the scientific steering committee:


Hannah Christensen

Hugo Lambert (University of Exeter)

Laura Mansfield (Stanford)

Romain Roehrig (CNRM, Météo-France and CNRS, Toulouse, France)


And the local organising committee:


Bobby Antonio

Hannah Christensen

Lilli Freischem

Edward Groot

Simon Michel

Greta Miller

Janet Sadler

Zhixiao Zhang


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