Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 17
Articles | Volume 18, issue 17
https://doi.org/10.5194/gmd-18-5549-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-5549-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 17
Model description paper
 | 
04 Sep 2025
Model description paper |  | 04 Sep 2025

CRITER 1.0: a coarse reconstruction with iterative refinement network for sparse spatio-temporal satellite data

Matjaž Zupančič Muc, Vitjan Zavrtanik, Alexander Barth, Aida Alvera-Azcarate, Matjaž Ličer, and Matej Kristan

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Short summary
Accurate sea surface temperature data (SST) are crucial for weather forecasting and climate modeling, but satellite observations are often incomplete. We developed a new method called CRITER, which uses machine learning to fill in the gaps in SST data. Our two-stage approach reconstructs large-scale patterns and refines details. Tested on Mediterranean, Adriatic, and Atlantic sea data, CRITER outperforms current methods, reducing errors by up to 44 %.
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