EGU2020-22676
https://doi.org/10.5194/egusphere-egu2020-22676
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Compatible finite element methods and parallel-in-time schemes for numerical weather prediction.

Jemma Shipton1, Colin Cotter2, Tom Bendall3, Thomas Gibson4, Lawrence Mitchell5, David Ham2, and Beth Wingate1
Jemma Shipton et al.
  • 1University of Exeter, UK
  • 2Imperial College London, UK
  • 3Met Office, UK
  • 4Naval Research Laboratory, Monterey, California, USA
  • 5Durham University, UK

I will describe Gusto, a dynamical core toolkit built on top of the Fire- drake finite element library; present recent results from a range of test cases and outline our plans for future code development.

Gusto uses compatible finite element methods, a form of mixed finite element methods (meaning that different finite element spaces are used for different fields) that allow the exact representation of the standard vector calculus identities div-curl=0 and curl-grad=0. The popularity of these methods for numerical weather prediction is due to the flexibility to run on non-orthogonal grid, thus avoiding the communication bottleneck at the poles, while retaining the necessary convergence and wave propagation prop- erties required for accuracy.

Although the flexibility of the compatible finite element spatial discreti- sation improves the parallel scalability of the model it does not solve the parallel scalability problem inherent in spatial domain decomposition: we need to find a way to perform parallel calculations in the time domain. Ex- ponential integrators, approximated by a near optimal rational expansion, offer a way to take large timesteps and form the basis for parallel timestep- ping schemes based on wave averaging. I will describe the progress we have made towards implementing these schemes in Gusto.

How to cite: Shipton, J., Cotter, C., Bendall, T., Gibson, T., Mitchell, L., Ham, D., and Wingate, B.: Compatible finite element methods and parallel-in-time schemes for numerical weather prediction., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22676, https://doi.org/10.5194/egusphere-egu2020-22676, 2020

Displays

Display file