Evaluation of Python Libraries for Visualization of Weather Fields
DOI:
https://doi.org/10.5753/reic.2026.7493Keywords:
Graphics libraries evaluation, Visualization, Python language, Atmospheric models, BRAMSAbstract
BRAMS forecasting workflows generate multidimensional atmospheric fields that are post-processed with legacy GrADS scripts, which limits integration with current web-oriented dissemination pipelines. This paper investigates a Python-based alternative for the final visualization stage of this workflow. We implemented a controlled qualitative comparative study in which Cartopy, Plotly, Bokeh, and Folium were evaluated under the same preprocessing conditions, using BRAMS outputs and equivalent geographic and variable selections. The assessment followed an explicit framework based on functional coverage, interactivity, integration effort, and output suitability. Results showed a consistent trade-off between projection/cartographic quality and interactive delivery. In the evaluated scenarios, the combination of Folium, Matplotlib, and geojsoncontour provided the best balance for interactive contour-based map dissemination. As an application contribution, we integrated this pipeline into a Streamlit interface that enables non-programmer users to explore variables and pressure levels with real-time visual feedback. These findings provide a reproducible basis for updating BRAMS visualization workflows while preserving operational usefulness.
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