Articles | Volume 7-osr10
https://doi.org/10.5194/sp-7-osr10-7-2026
https://doi.org/10.5194/sp-7-osr10-7-2026
30 Sep 2026
 | OSR10 | Chapter 2.4
 | 30 Sep 2026 | OSR10 | Chapter 2.4

Towards a multi-product methodology for calculating the ocean monitoring indicator of SST extremes in the IBI region

Álvaro de Pascual Collar, Axel Alonso Valle, Alex Gallardo, Marta de Alfonso Alonso-Muñoyerro, Begoña Pérez Gómez, Stefania Ciliberti, and Marcos G. Sotillo

Data sets

Iberia Biscay Ireland Sea Surface Temperature extreme from Reanalysis EU Copernicus Marine Service Product https://doi.org/10.48670/moi-00254

European North West Shelf/Iberia Biscay Irish Seas - High Resolution ODYSSEA L4 Sea Surface Temperature Analysis EU Copernicus Marine Service Product https://doi.org/10.48670/moi-00152

Iberia Biscay Ireland sea surface temperature extreme variability mean and anomaly (observations) EU Copernicus Marine Service Product https://doi.org/10.48670/moi-00255

Global Ocean Physics Reanalysis EU Copernicus Marine Service Product https://doi.org/10.48670/moi-00021

Atlantic-Iberian Biscay Irish-Ocean Physics Reanalysis EU Copernicus Marine Service Product https://doi.org/10.48670/moi-00029

Atlantic-Iberian Biscay Irish-Ocean Physics Analysis and Forecast EU Copernicus Marine Service Product https://doi.org/10.48670/moi-00027

Global Ocean Physics Analysis and Forecast EU Copernicus Marine Service Product https://doi.org/10.48670/moi-00016

European North West Shelf/Iberia Biscay Irish Seas - High Resolution L4 Sea Surface Temperature Reprocessed EU Copernicus Marine Service Product https://doi.org/10.48670/moi-00153

Model code and software

Taylor diagram in python based on Taylor (2001) Mabel Calim Costa https://github.com/mabelcalim/Taylor_diagram

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Short summary
This study improves the monitoring of extreme sea surface temperature events in the Iberia–Biscay–Ireland region. We tested new data sources and combined information from different models and satellites to provide more consistent results and characterize inter-product spread. The findings show that these methods make the indicator more reliable and useful for supporting climate and ocean management decisions.
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