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Multiscale Spatiotemporal Meteorological Drought Prediction: A Deep Learning Approach

23.05.24 | Cuca Margoux

by Jia-Li Zhang, Xiao-Meng Huang and Yu-Ze Sun


Reliable monitoring and thorough spatiotemporal prediction of meteorological drought are crucial for early warning and decision-making regarding drought-related disasters. The utilisation of multiscale methods is effective for a comprehensive evaluation of drought occurrence and progression, given the complex nature of meteorological drought. Nevertheless, the nonlinear spatiotemporal features of meteorological droughts, influenced by various climatological, physical and environmental factors, pose significant challenges to integrated prediction that considers multiple indicators and time scales.

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