Significant advancement in subseasonal-to-seasonal summer precipitation ensemble forecast skills in China mainland through an innovative hybrid CSG-UNET method

Reliable Subseasonal-to-Seasonal (S2S) forecasts of precipitation are critical for disaster prevention and mitigation. In this study, an innovative hybrid method CSG-UNET combining the UNET with the censored and shifted gamma distribution based ensemble model output statistic (CSG-EMOS), is proposed...

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Bibliographic Details
Published in:	Environmental Research Letters
Main Authors:	Yang Lyu, Shoupeng Zhu, Xiefei Zhi, Jingyu Wang, Yan Ji, Yi Fan, Fu Dong
Format:	Article
Language:	English
Published:	IOP Publishing 2024-01-01
Subjects:	subseasonal precipitation forecast deep learning method extreme precipitation probabilistic precipitation forecast
Online Access:	https://doi.org/10.1088/1748-9326/ad5577

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