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Data for “Radar Quantitative Precipitation Estimation Using Multiple Deep Learning Models on Hainan Island”
This dataset consists of polarimetric radar observations and rain gauge measurements collected over Hainan Island during 2020–2023, used for deep learning–based radar quantitative precipitation estimation (QPE). Dataset I.xlsx contains point-based radar-
File Size107.7 MB
Data TypeDataset
Published2026
Licensecc-by-4.0
Total Views77
Total Downloads41
This dataset consists of polarimetric radar observations and rain gauge measurements collected over Hainan Island during 2020–2023, used for deep learning–based radar quantitative precipitation estimation (QPE).
Dataset I.xlsx contains point-based radar-gauge paired data, including polarimetric radar variables (reflectivity ZH, differential reflectivity ZDR, specific differential phase KDP) from two elevation angles, hourly rain rate.
Dataset II_radar.npy stores 9×9 spatial grid radar patches centered at each rain gauge, including two elevation ZH, ZDR, and KDP fields, designed for convolutional neural network (CNN) QPE models.
Dataset II_gauge.npy provides the ground‑truth rainfall intensity corresponding to the radar samples, serving as the training and validation target for all deep learning models.
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Files are hosted on the source repository. Click download to access the full dataset.
Zhou, Yuanhao (2026). Data for “Radar Quantitative Precipitation Estimation Using Multiple Deep Learning Models on Hainan Island”. https://doi.org/10.5281/zenodo.19511550