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

Autor(en)
Aiko Voigt, Petra Schwer, Noam von Rotberg, Nicole Knopf
Abstrakt

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(en)
Institut für Meteorologie und Geophysik
Externe Organisation(en)
Otto-von-Guericke-Universität Magdeburg, Karlsruher Institut für Technologie
Journal
Geoscientific Model Development
Band
15
Seiten
7489-7504
Anzahl der Seiten
16
ISSN
1991-959X
DOI
https://doi.org/10.5194/gmd-15-7489-2022
Publikationsdatum
10-2022
Peer-reviewed
Ja
ÖFOS 2012
105204 Klimatologie
ASJC Scopus Sachgebiete
Allgemeine Erdkunde und Planetologie, Modelling and Simulation
Link zum Portal
https://ucrisportal.univie.ac.at/de/publications/98ce96b7-7897-4f14-950f-3519e528b651