CUBE: Cubed-sphere projection for adaptive mesh generation in spherical coordinates

We present CUBE , an open-source Python framework for generating adaptive, non-singular meshes on the sphere using a cubed-sphere projection. The software maps spherical slices to Cartesian faces of an inscribed cube, avoiding the pole singularities inherent to latitude–longitude grids and producing quasi-uniform element sizes across the globe. A core feature of CUBE is error-driven spatial adaptation: the mesh is refined according to an estimator based on an approximation of the H 1 -seminorm of the topography discretization error, which concentrates resolution where terrain gradients are large. The implementation leverages numpy and scipy for efficient array operations, integrates gmsh via its Python API for meshing, and supports standard geospatial input (e.g., GTOPO30 digital elevation models). CUBE is intended as an extensible tool to produce high-quality input meshes for atmospheric and geophysical models, improving accuracy while reducing computational costs through targeted refinement.

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Publication Details

Journal
SoftwareX
Published
2026-01-16
DOI
https://doi.org/10.1016/j.softx.2026.102514
Primary Topic
Historical Geography and Cartography
Type
article
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article

CUBE: Cubed-sphere projection for adaptive mesh generation in spherical coordinates

Federico Gatti
SoftwareX
Historical Geography and Cartography
article

CUBE: Cubed-sphere projection for adaptive mesh generation in spherical coordinates

Federico Gatti
article en

Abstract

We present CUBE , an open-source Python framework for generating adaptive, non-singular meshes on the sphere using a cubed-sphere projection. The software maps spherical slices to Cartesian faces of an inscribed cube, avoiding the pole singularities inherent to latitude–longitude grids and producing quasi-uniform element sizes across the globe. A core feature of CUBE is error-driven spatial adaptation: the mesh is refined according to an estimator based on an approximation of the H 1 -seminorm of the topography discretization error, which concentrates resolution where terrain gradients are large. The implementation leverages numpy and scipy for efficient array operations, integrates gmsh via its Python API for meshing, and supports standard geospatial input (e.g., GTOPO30 digital elevation models). CUBE is intended as an extensible tool to produce high-quality input meshes for atmospheric and geophysical models, improving accuracy while reducing computational costs through targeted refinement.

SoftwareXVol. 33
ETH Zurich (CH)
Openalex Percentile: Top 88%
Historical Geography and Cartography
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CUBE: Cubed-sphere projection for adaptive mesh generation in spherical coordinates — Federico Gatti · SoftwareX (2026) | TGRS Research Map | TGRS