Articles | Volume 29, issue 3
https://doi.org/10.5194/hess-29-799-2025
https://doi.org/10.5194/hess-29-799-2025
Research article
 | 
13 Feb 2025
Research article |  | 13 Feb 2025

Refining remote sensing precipitation datasets in the South Pacific with an adaptive multi-method calibration approach

Óscar Mirones, Joaquín Bedia, Sixto Herrera, Maialen Iturbide, and Jorge Baño Medina

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This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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Cited articles

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We devised an adaptive method for calibrating remote sensing precipitation in the South Pacific. By classifying data into weather types and applying varied techniques, we achieve improved calibration. Results showed enhanced accuracy in mean and extreme precipitation indices across locations. The method offers customization options and effectively addresses intense rainfall events. Its versatility allows for application in diverse scenarios, supporting a better understanding of climate impacts.
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