Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/gmd-2017-47
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Model description paper
11 Apr 2017
Review status
This discussion paper is a preprint. A revision of the manuscript was accepted for the journal Geoscientific Model Development (GMD).
Shingle 2.0: generalising self-consistent and automated domain discretisation for multi-scale geophysical models
Adam Candy and Julie Pietrzak Environmental Fluid Mechanics Section, Faculty of Civil Engineering and Geosciences, Delft University of Technology, The Netherlands
Abstract. The approaches taken to describe and develop spatial discretisations of the domains required for geophysical simulation models are commonly ad hoc, model or application specific and under-documented. This is particularly acute for simulation models that are flexible in their use of multi-scale, anisotropic, fully unstructured meshes where a relatively large number of heterogeneous parameters are required to constrain their full description. As a consequence, it can be difficult to reproduce simulations, ensure a provenance in model data handling and initialisation, and a challenge to conduct model intercomparisons rigorously.

This paper takes a novel approach to spatial discretisation, considering it much like a numerical simulation model problem of its own. It introduces a generalised, extensible, self- documenting approach to carefully describe, and necessarily fully, the constraints over the heterogeneous parameter space that determine how a domain is spatially discretised. This additionally provides a method to accurately record these constraints, using high-level natural language based abstractions, that enables full accounts of provenance, sharing and distribution. Together with this description, a generalised consistent approach to unstructured mesh generation for geophysical models is developed, that is automated, robust and repeatable, quick-to-draft, rigorously verified and consistent to the source data throughout. This interprets the description above to execute a self-consistent spatial discretisation process, which is automatically validated to expected discrete characteristics and metrics.


Citation: Candy, A. and Pietrzak, J.: Shingle 2.0: generalising self-consistent and automated domain discretisation for multi-scale geophysical models, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-47, in review, 2017.
Adam Candy and Julie Pietrzak
Adam Candy and Julie Pietrzak
Adam Candy and Julie Pietrzak

Viewed

Total article views: 490 (including HTML, PDF, and XML)

HTML PDF XML Total BibTeX EndNote
361 103 26 490 6 29

Views and downloads (calculated since 11 Apr 2017)

Cumulative views and downloads (calculated since 11 Apr 2017)

Viewed (geographical distribution)

Total article views: 490 (including HTML, PDF, and XML)

Thereof 489 with geography defined and 1 with unknown origin.

Country # Views %
  • 1

Saved

Discussed

Latest update: 18 Oct 2017
Publications Copernicus
Download
Short summary
Shingle is a generalised and accessible framework for model-independent and self-consistent geophysical domain discretisation, which accurately conform to fractal-like bounds and at varyingly resolved spatial scales. The full heterogeneous set of constraints are necessarily completely described by an extensible, hierarchical formal grammar with an intuitive natural language basis for geophysical domain features to achieve robust reproduction and consistent model intercomparisons.
Shingle is a generalised and accessible framework for model-independent and self-consistent...
Share