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<!DOCTYPE html>
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<html>
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<head>
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<meta charset="utf-8" />
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<title>UXarray: Xarray extensions for unstructured grids</title>
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<style>
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body { font-family: Georgia, serif; line-height: 1.45; margin: 2rem; }
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h1, h2, h3 { font-family: Helvetica, Arial, sans-serif; }
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code, pre { font-family: Menlo, Consolas, monospace; background: #f6f8fa; padding: 2px 4px; }
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figure { margin: 1rem 0; }
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figcaption { font-size: 0.9rem; color: #666; }
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</style>
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</head>
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<body>
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<h1>UXarray: Xarray extensions for unstructured grids</h1>
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<h2>(1) Overview</h2>
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<h3>Title</h3>
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<p>UXarray: Xarray extensions for unstructured climate and weather data</p>
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<h3>Paper Authors</h3>
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<ul>
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<li><strong>Rajeev Jain</strong> (Lead Author), University/Institution TBD, ORCID: TBD</li>
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<li>Aaron Zedwick, Affiliation TBD</li>
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<li>David Ahijevych, NCAR (TBD)</li>
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<li>Anissa Zacharias, UCAR (TBD)</li>
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<li>David Galicia, Affiliation TBD</li>
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<li>Orhan Eroglu, Affiliation TBD</li>
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<li>Paul Ullrich, UC Davis (TBD)</li>
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<li>Philip Chmielowiec, Affiliation TBD</li>
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<li>Hongyu Chen, UC Davis (TBD)</li>
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<li>Kristen Thyng, Affiliation TBD</li>
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<li>Mario A. Rodriguez, NCAR (TBD)</li>
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<li>Maxime Liquet, Affiliation TBD</li>
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<li>Michaela Sizemore, Affiliation TBD</li>
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<li>Katelyn FitzGerald, Affiliation TBD</li>
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<li>Filipe Fernandes, Affiliation TBD</li>
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<li>... (additional contributors from git history)</li>
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</ul>
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<h3>Abstract</h3>
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<p>
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UXarray provides an Xarray-compatible interface for loading, analyzing, and
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visualizing data on unstructured grids. It standardizes access to common grid
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representations (UGRID, MPAS, Exodus, ICON, SCRIP, ESMF, FESOM, HEALPix) and
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exposes familiar DataArray/Dataset accessors for grid-aware operations, such as
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subset, remap, cross-section extraction, and zonal statistics.
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</p>
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<h3>Keywords</h3>
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<p>unstructured grids; xarray; UGRID; MPAS; Exodus; ICON; climate; geoscience; visualization</p>
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<h3>Introduction</h3>
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<p>
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Many next-generation climate and weather models produce data on unstructured
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meshes. While Xarray provides a robust interface for labeled N-dimensional
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arrays, it does not natively understand unstructured grid topology. UXarray
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bridges this gap by pairing Xarray objects with a Grid, enforcing UGRID-style
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conventions, and providing operations that respect mesh geometry and
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connectivity.
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</p>
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<h3>Implementation and Architecture</h3>
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<p>
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UXarray adds grid-aware accessors to UxDataArray and Grid, with core modules for
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I/O, subsetting, remapping, plotting, and cross-sections. Figure 1 outlines the
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major components.
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</p>
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<figure>
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<img src="images/fig1.svg" alt="Overview diagram" width="640" />
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<figcaption>Figure 1: UXarray components and data flow.</figcaption>
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</figure>
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<pre><code>
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import uxarray as ux
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uxgrid = ux.open_grid("grid.ug")
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uxds = ux.open_dataset("grid.ug", "psi.nc")
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# Cross-section along a geodesic
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cs = uxds["psi"].cross_section(start=(-45, -45), end=(45, 45), steps=200)
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</code></pre>
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<h3>Case Studies / Example Applications</h3>
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<p>
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We demonstrate: (1) cross-section sampling along geodesics and constant
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parallels/meridians; (2) zonal means; (3) remapping workflows. Figure 2 shows a
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schematic cross-section sampling trajectory.
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</p>
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<figure>
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<img src="images/fig2.svg" alt="Cross-section sampling" width="640" />
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<figcaption>Figure 2: Sampling a field along a geodesic arc (steps shown along the path).</figcaption>
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</figure>
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<h3>Conclusions</h3>
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<p>
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UXarray brings consistent, grid-aware operations to Xarray, enabling reusable
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analysis patterns across diverse unstructured formats. It unifies I/O and
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computation through a minimal, UGRID-consistent contract, supporting common
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geoscience analyses.
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</p>
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<h3>Quality Control</h3>
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<p>
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UXarray includes unit tests, continuous integration, pre-commit hooks and style
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checks. It runs on Linux (and macOS/Windows via CI) and targets Python 3.10+.
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</p>
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<h2>(2) Availability</h2>
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<h3>Operating System(s)</h3>
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<p>Linux, macOS, Windows (CI tested)</p>
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<h3>Programming Language</h3>
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<p>Python 3.10+</p>
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<h3>Dependencies</h3>
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<p>Key runtime dependencies include: antimeridian, cartopy, dask, datashader,
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geoviews, holoviews, matplotlib, netcdf4, numba, numpy (&lt;2.3), pandas,
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pyarrow, requests, scikit-learn, scipy, shapely, spatialpandas, geopandas,
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xarray, hvplot, healpix, polars, pyproj.</p>
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<h3>List of Contributors</h3>
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<p>See the Git commit history for a full list of contributors. We acknowledge
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all listed authors above as core contributors.</p>
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<h3>Software Location</h3>
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<ul>
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<li><strong>Archive</strong>: TBD (e.g., Zenodo DOI)</li>
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<li><strong>Code Repository</strong>: <a href="https://github.com/UXARRAY/uxarray">https://github.com/UXARRAY/uxarray</a></li>
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</ul>
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<h2>(3) Reuse Potential</h2>
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<h3>General Applicability</h3>
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<p>
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UXarray is broadly applicable to global geoscience, oceanography, and weather
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model output on unstructured meshes. It is licensed under the BSD-3 license,
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with active issue tracking, contribution guidelines, and documentation.
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</p>
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<h3>Acknowledgements</h3>
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<ul>
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<li><strong>Funding Statement</strong>: TBD</li>
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<li><strong>Competing Interests</strong>: The authors declare no competing interests.</li>
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</ul>
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<h3>References</h3>
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<ol>
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<li>UGRID conventions and related resources.</li>
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<li>Xarray documentation and APIs.</li>
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<li>Model and format references (MPAS, Exodus, ICON, ESMF, FESOM, HEALPix).</li>
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</ol>
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</body>
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</html>

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