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CRiSM Workshop on "Fusing Simulation with Data Science"

Welcome to Fusing Simulation with Data Science 2023

Jointly organized with Met Office and ECMWF

The workshop will be held at the Department of Statistics, University of Warwick, UK from 18th to 19th July 2023.

With our understanding of weather phenomena and their interaction with sea currents, pollutants etc, we have been able to create very complex and elaborate simulator models for numerical weather predictions (NWP). These models rely on specialised “classical” solvers, which are handcrafted to simulate a particular physical process. While accurate and reliable, these solvers produce deterministic solutions, can be quite slow and can only be simulated on a rather restrictive coarse grid for global or regional simulations. Machine learning and computational statistics, broadly data science, has been fused with these classical simulations to assimilate observed data (data-assimilation), to produce probabilistic simulations (stochastic parameterisation or ensemble prediction), to fill the gap between these classical simulations to km-scale weather predictions (statistical downscaling).

Data driven approaches have also been used to create neural PDE solvers for weather forecasting which are competitive with, and in some cases exceed the performance of, traditional NWP models but at a fraction of the computational cost.

The first edition of this workshop on “Fusing simulation with data science”, jointly organised by Dept. of statistics in University of Warwick and Met Office, aims to provide an up-to-date snapshot of this fusion between the paradigm of classical simulations and data science and to facilitate discussion among data scientists (probabilist, applied mathematicians, statisticians and machine learners) and meteorologists about the current opportunities and challenges.

Thematic areas that we expect to be covered in this workshop and we invite contributions include:

  1. Data Assimilation
  2. Statistical downscaling
  3. Spatio-temporal statistics and model emulation
  4. Data-driven NWP, PDE solvers, and operator learning
  5. Extreme Values and climate change

Attendance and Registration

While the main focus of the workshop is towards an in-person event, remote attendance will be possible. Attendees would be provided with free lunch and drinks during the coffee break.

To attend you need to register.

(Registration closes on 15th June.)

If you want to present your work as a contributed speaker or in the poster session please submit title and abstract when you register. If you want to present your work please register and submit your work by 15th May.

Organising Committee: Ritabrata Dutta (University of Warwick), Tom Dunstan (Met Office), Matthew Chantry (ECMWF), Peter Watson (University of Bristol)

Contact: Ritabrata Dutta,