TriCCo v1.1.0 – a cubulation-based method for computing connected components on triangular grids

Author(s)
Aiko Voigt, Petra Schwer, Noam von Rotberg, Nicole Knopf
Abstract

We present a new method to identify connected components on triangular grids used in atmosphere and climate models to discretize the horizontal dimension. In contrast to structured latitude-longitude grids, triangular grids are unstructured and the neighbors of a grid cell do not simply follow from the grid cell index. This complicates the identification of connected components compared to structured grids. Here, we show that this complication can be addressed by involving the mathematical tool of cubulation, which allows one to map the 2-D cells of the triangular grid onto the vertices of the 3-D cells of a cubical grid. Because the latter is structured, connected components can be readily identified by previously developed software packages for cubical grids. Computing the cubulation can be expensive, but, importantly, needs to be done only once for a given grid. We implement our method in a Python package that we name TriCCo and make available via pypi, gitlab, and zenodo. We document the package and demonstrate its application using simulation output from the ICON atmosphere model. Finally, we characterize its computational performance and compare it to graph-based identifications of connected components using breadth-first search. The latter shows that TriCCo is ready for triangular grids with up to 500 000 cells, but that its speed and memory requirement should be improved for its application to larger grids.

Organisation(s)
Department of Meteorology and Geophysics
External organisation(s)
Otto-von-Guericke-Universität Magdeburg, Karlsruher Institut für Technologie
Journal
Geoscientific Model Development
Volume
15
Pages
7489-7504
No. of pages
16
ISSN
1991-959X
DOI
https://doi.org/10.5194/gmd-15-7489-2022
Publication date
10-2022
Peer reviewed
Yes
Austrian Fields of Science 2012
105204 Climatology
ASJC Scopus subject areas
General Earth and Planetary Sciences, Modelling and Simulation
Portal url
https://ucrisportal.univie.ac.at/en/publications/98ce96b7-7897-4f14-950f-3519e528b651