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Abstract Short-term precipitation nowcasting serves as an indispensable technical support for the early warning and risk management of meteorological hazards. To improve the nowcasting accuracy by leveraging complementary information from multi-source data, this study proposes a precipitation nowcasting model based on multi-source data fusion and efficient additive attention (EAA-MNFP).
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