A new method for predicting precipitation δ18O distribution based on deep learning and spatio-temporal clustering

Yang Li, Siyuan Huo, Bin Ma, Bingbing Pei, Qiankun Tan, Qing Guo, Deng Wang, Longbiao Yu
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Abstract

Predicting precipitation δ18O accurately is crucial for understanding water cycles, paleoclimates, and hydrological applications. Yet, forecasting its spatio-temporal distribution remains challengi...
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基于深度学习和时空聚类的降水δ18O分布预测新方法
准确预测降水δ18O对于了解水循环、古气候和水文应用至关重要。然而,预测其时空分布仍然是一项挑战。
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