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ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Data and trained models — Deep-learning statistical downscaling of daily precipitation over West Africa

Authors: Sagna, David; Lguensat, Redouane; Diatta, Samo;

Data and trained models — Deep-learning statistical downscaling of daily precipitation over West Africa

Abstract

Supporting data and trained model weights for the study on deep-learning statistical downscaling of daily precipitation over West Africa (ERA5 0.25° → IMERG 0.1°, factor 2.5×), submitted to Environmental Data Science (Cambridge University Press). Files: arrays_01deg.npz — cached model outputs and IMERG observations on the 0.1° evaluation grid (7 configurations + observations), allowing reproduction of all figures and metric tables without re-running the networks. weights.zip — the six trained PyTorch models (U-Net Simple/SE/CBAM and their cGAN-fine-tuned variants). The replication code is available on GitHub: github.com/sagna1/downscaling-westafrica-eds. Raw predictors (ERA5) and target (IMERG Final Run V06) are openly available from the C3S Climate Data Store and NASA GES DISC respectively.

Related Organizations
Keywords

conditional GAN, West Africa, quantile mapping, deep learning, ERA5, West African Monsoon, precipitation, IMERG, statistical downscaling, U-Net

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average